Maluuba, a Microsoft company working towards general artificial intelligence, recently released a new open dialogue dataset based on booking a vacation - specifically, finding flights and a hotel.
Source: Infoq
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A year and a half ago, I dropped out of one of the best computer science programs in Canada. I started creating my own data science master's program using online resources.
Source: Medium26856
"Artificial intelligence (AI) and machine learning (ML) have rapidly matured over the years and are already the norm in many fields, helping companies deploy smart systems of engagement to improve efficiency, enhance security, gain insights, and deliver superior customer experiences," writes Aan Chauhan.
Source: Congnizant5070
Demand for skilled data scientists continues to be sky-high, with IBM recently predicting that there will be a 28% increase in the number of employed data scientists in the next two years.
Source: Forbes15240
Alteryx, fresh off its IPO, introduces Alteryx Connect, a data catalog/governance product based off its previously undisclosed acquisition of Semanta. Alteryx is also announcing its acquisition of Yhat, a startup specializing in data science development, management, and deployment.
Source: ZDnet3201
Microsoft's cloud-based virtual machine for big data analytics is now available in a version running on Windows Server 2016.
Source: Eweek3336
Data science and data analytics: people working in the tech field or other related industries probably hear these terms all the time, often interchangeably.
Source: Insidebigdata11946
Understanding machine learning & data science is easy. There are numerous open courses which you can take up right now and get started. But, acquiring in-depth knowledge of a subject requires extra effort.
Source: HOB Team13935
Machine learning algorithms can be divided into 3 broad categoriesā??-ā??supervised learning, unsupervised learning, and reinforcement learning.
Source: kdnuggets4248
Artificial Intelligence (AI) is one of the most transformative forces of our times. While there may be debate whether AI will transform our world in good or evil ways, something we can all agree on is that AI would be nothing without big data.
Source: Forbes3747
One of the common problems people face in learning R is lack of a structured path. They don't know, from where to start, how to proceed, which track to choose?
Source: Analytics Vidya18102
Data science is just that - science. Specially trained individuals well-versed in how to break down big data sets and interpret their meaning are in high demand.
Source: TNW3909
How do Data Science and DevOps fit together? In this article, Richard Gall explains why integrating Data Science with your DevOps can lead to a better and smarter business.
Source: jaxenter3315
The skills of data experts are becoming outdated as the industry evolves. If you're looking to learn data science - quickly - then you're in luck.
Source: jaxenter2748
Since all of the libraries are open sourced, we have added commits, contributors count and other metrics from Github, which could be served as a proxy metrics for library popularity.
Source: Kdnuggets5493
Google's Ground Truth team recently announced a new deep learning model for the automatic extraction of information from geo-located image files to improve Google Maps.
Source: Infoq4944
Some people have relied on "common sense" to brand an entire religion as dangerous-but rigorous analysis proves they're wrong
Source: Scientific American2469
Today, Big Data gives us unprecedented insights and opportunities across all industries from healthcare to financial to manufacturing and more. But, it also raises concerns and questions that must be addressed.
Source: Forbes3015
What's the one thing that makes a great data leader?
Source: Data-informed2355
Data Scientists are in big demand! We review career pathways, relevant data science skills, and how you can learn them at no cost.
Source: KDnuggets2664
Spring. Rejuvenation. Rebirth. Everything's blooming. And, of course, people want free ebooks. With that in mind, here's a list of 10 free machine learning and data science titles to get your spring reading started right.
Source: KDnuggets4704
From gaining the right skills to acing your first interview, these resources can help put you on the right track
Source: PCworld2691
Data scientists in the marketing world have something in common with the nerd characters on police-procedural TV shows, according to speakers at a DigitasLBi-hosted event in Singapore last week.
Source: Campaign Asia3618
As data analytics matures from a science into a technology, companies are shifting their focus toward making products out of the advanced models generated by their data science organizations.
Source: A silicon ANGLE3912
Interview: Tom Smith, managing director of the new body in the Office of National Statistics, says it can do a lot to support policy makers in understanding complex issues
Source: ukauthority3030
The growth of AI and large data sets pose great risks to privacy. Two top experts explain the issues to help your company manage this crucial part of the technology landscape.
Source: ZDnet2490
Data science is the theory and practice powering the data-driven transformations we are seeing across industry and society today. Artificial intelligence (AI), self-driving cars, and predictive analytics are just a few of the breakthroughs that have been made thanks to our ever-growing ability to collect and analyze data.
Source: Data Informed8130
Machine Learning applications include evaluation of driver condition or driving scenario classification through data fusion from different external and internal sensors. We examine different algorithms used for self-driving cars.
Source: KDnuggets7062
Leaders sometimes ask questions that get in the way of solving the problem that really matters to them. We can learn a lot from a real-life example of two business titans.
Source: Forbes3126
Harvard will offer a Master of Science (SM) degree in Data Science beginning in fall of 2018. The new degree, under the joint academic leadership of the faculties of Computer Science in the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), and of Statistics in the Faculty of Arts and Sciences (FAS), will train students in the rapidly growing field of data science.
Source: HBR5718
US- and Bangalore-based Julia Computing, a provider of open source language for data science and machine learning, has received $4.6 million (Rs 30 crore) in seed funding from US-based investment firms General Catalyst and Founder Collective.
Source: VCC10734
Data Science is a comparatively new domain which most of us is not thorough with, agreed?
Source: Aircto2796
IDE stands for Integrated Development Environment. It's a coding tool which allows you to write, test and debug your code in an easier way, as they typically offer code completion or code insight by highlighting, resource management, debugging tools
Source: Datacamp10251
Start with y. Concentrate on formalizing the predictive problem, building the workflow, and turning it into production rather than optimizing your predictive model. Once the former is done, the latter is easy.
Source: medium4128
Since February I have been working on a video course with Packt Publishing, and the course is now published.
Source: NTguardian5901
The cyberthreat landscape evolves at breakneck speed. While cybercriminals are able to compromise a system in hours or minutes, the reaction of companies usually takes months or even years.
Source: Pandasecurity11121
What does it take to compete in a global arena in which retail and cloud are increasingly intertwined? Domain-specific data science and machine learning for the masses, according to Alibaba.
Source: ZDnet5664
A lot of people reach out to me. They needs jobs. But they are asking about school.
Source: Forbes3366
DataScience.com customers can now benefit from The Data Incubator's comprehensive data science training in the DataScience.com Platform.
Source: Global Newswire4209
Most industries are struggling to find data science expertise, but Wall Street especially has particularly keen to hire in this area. Data has always been a big part of the finance industry, and over the last few years, top financial services firms have ramped up their spending, investing millions of dollars to recruit and train data scientists.
Source: Efinancial Career3312
AI, or artificial intelligence, has taken root in biotech. In this article, a contributor explores its newfound niches in the industry.
Source: Labiotech9816
Coming soon: 61st World Statistics Congress Marrakech, TDWI Anaheim, ICML Sydney, KDD-2017 Halifax, JupyterCon NYC, Big Data Innovation Summit Boston, and many more.
Source: KDnuggets10314
This course created by Data Weekends, Jose Portilla, and Francesco Mosconi is designed to provide a complete introduction to Deep Learning. It is aimed at beginners and intermediate programmers and data scientists who are familiar with Python and want to understand and apply Deep Learning techniques to a variety of problems.
Source: Medium11124
Want to be a data scientist? Third-level institutions and full-time education aren't the only way you can learn essential data science skills.
Source: Siliconrepublic8100
The chief data officer's next challenge may be to find storytellers who can explain machine learning for data science to decision-makers in the organization.
Source: Techtarget6966
So, you want to build a data science team? Here's some stuff to think about. Before long, just like this stock photo, you'll have a team of weird orange people with big bulbous heads, who can sit around a table looking at an enormous hologram of a simple bar chart.
Source: Econsultancy5148
In their HBR Big Idea feature, Erik Brynjolfsson and Andrew McAfee argue that AI and machine learning will soon become "general-purpose technologies," as significant as electricity or the internal combustion engine. They represent a landmark change in our technical capabilities and will power the next wave of economic growth.
Source: HBR8373
Artificial Intelligence is colossally hyped these days, but the dirty little secret is that it still has a long, long way to go. Sure, A.I. systems have mastered an array of games, from chess and Go to "Jeopardy" and poker, but the technology continues to struggle in the real world. Robots fall over while opening doors, prototype driverless cars frequently need human intervention, and nobody has yet designed a machine that can read reliably at the level of a sixth grader, let alone a college student. Computers that can educate themselves - a mark of true intelligence - remain a dream.
Source: NY Times4347
Data science is complex. Let us help break it down for you in this bundle where you can learn everything a data scientist needs to know before jumping into it as a career.
Source: Techrepublic3291
July 30 marks the United Nations' World Day Against Trafficking in Persons, a day focused on ending the criminal exploitation of children, women and men for forced labor or sex work
Source: Scientificamerican2976
In recent years, influencer marketing has established itself as a highly-effective method for brands to build and engage with audiences on social media. It is well-documented that influencers and their authentic content creation can help brands grab the attention of consumers and gain their trust, but the question has remained: Does influencer marketing actually directly impact sales at scale?
Source: Forbes3759
Demand for developers with data science skills continues to grow. Here's what you need to learn to break into a career in the field.
Source: Techrepublic3045
Many aspiring data scientists focus on doing Kaggle competitions as a way to build their portfolios. Kaggle is an excellent way to practice, but it should only be one of many avenues you use to work on data science projects.
Source: Dataquest2454
Machine Learning and AI are often heralded as the future of, well, every industry ever. But what about the future of Machine Learning itself? Sebastian Raschka, applied machine learning and deep learning researcher at Michigan State University and the author of Packt's best-selling book Python Machine Learning, takes a look at what's changed the most in the last few years and what's next on the horizon - here's a hint, it's not robots taking over the world.
Source: CBR4995
As the integration of Artificial Intelligence, Machine Learning and Big Data in the workplace is becoming the new norm, concerns are increasing over how the technology could affect employee performance, job security and the adaptation and reliance of technology in the legal industry.
Source: Inside Counsel4260
Citing the need for jobs of the future, Gov. Andrew Cuomo on Thursday announced $22.5 million in state support for the creation of a Rochester Data Science Consortium on the University of Rochester campus.
Source: Democratandchronicle3840
The state government on Wednesday announced it will establish a Centre of Excellence for Data Science and Artificial Intelligence (CoE-DS&AI), with Nasscom as the programme and implementation partner.
Source: ET Tech6291
There are many differing opinions on the impact of artificial intelligence (AI) on our worklives, from dazzling to dystopian.
Source: Forbes9744
Razorthink Inc., an innovator in Artificial Intelligence Data Science for the Enterprise, today announced Razorthink Big Brain, the first Deep Learning Data Science Platform that automates the data preparation, modeling, evaluation and deployment of Deep Learning solutions at scale. With Razorthink Big Brain, organizations can quickly generate Expert AIs that supercharge their data science efforts with superior big data predictive analytics and help businesses avoid blind spots by 'knowing what they don't know.'
Source: Globe News Wire4101
Data science is a vast, fascinating field. Analysis of datasets can be applied to multitudes of areas to improve people's quality of life. It would be difficult to find a better application of data science changing people's lives than Berlin-based menstrual and ovulation tracker Clue.
Source: Silicon Republic3723
Of course, this follows the basic laws of economics - supply and demand. The demand for data science is very high, while the supply is too low.
Source: Forbes7518
Businesses need to look for a diverse range of backgrounds, skills and experiences when hiring their analytics teams.
Source: Which-509330
An Interview with Sergey Nikolenko, Chief Scientist of Neuromation, a Blockchain for Artificial Intelligence company.
Source: Nextbigfuture7701
What is the role of machine learning in cyber security or networking security? originally appeared on Quora - the place to gain and share knowledge, empowering people to learn from others and better understand the world.
Source: Huffingtonpost2202
What is the role of machine learning in cyber security or networking security? originally appeared on Quora - the place to gain and share knowledge, empowering people to learn from others and better understand the world.
Source: Huffingtonpost6240
Data lakes didn't quite pan out so now it's all about an abstraction layer and machine learning to save the day. Hopefully, machine learning can cleanse your data on the fly since humans have proved repeatedly they aren't meticulous enough.
Source: ZD Net4875
While quick and dirty Google Trends is definitely not data science it can be useful for a sniff test. I was working on a client project today, when I thought I would look at search interest over time. Rails- weĆ?Ā¢??d expect to be tailing off a bit.
Source: Enterprise Irregulars10275
In this special guest feature, Kevin Safford, Sr. Director of Engineering for Umbel offers a no-nonsense look at how to answer the proverbial question "How can I become a data scientist." To understand how to become a data scientist, it's best to get on the same page on what data science is.
Source: Inside Bigdata9174
Machine learning and big data are having a positive impact on customer experience, as well as producing extensive benefits for banks.
Source: Information Age7779
Tech is facing a talent gap, in the absence of formal data science degrees at major universities. The assumption that only computer science majors have a place in the new economy is a "very shallow view," CA Technologies CEO Mike Gregoire said.
Source: CNBC8130
Given that data was held in such high regard even in the late 19th century, it is no surprise that this would be the case in the age of Internet and information overload. In fact, simply having data will no longer cut it; you need to know how to interpret it and how to derive actionable insights from it.
Source: The Hindu3075
Coupled with technology, data can transform the way businesses operate to stay ahead of their competitors.
Source: Daily Nation3162
It doesn't have a super-sexy moniker like KRACK or Heartbleed, but the spectre of the insider threat looms large for organisations, and has done so for as long as electricity, silicon, and computing have been paired up to store information.
Source: ZDNet2775
Accern, a New York-based data science start-up has today closed a $2.1 million Pre-Series A funding round led by private investors, including 26 Ventures' Managing Partner, Moshe Neuman.
Source: Forbes3201
DJ Patil, the chief data scientist under President Barack Obama, has joined Venrock Capital as an adviser. Patil has long been a proponent of using data science and artificial intelligence to solve some of the nation's biggest problems around areas including medicine, policing and the criminal justice system.
Source: TC3210
Really you want to upgrade your skills with the best Data Analytics, Development courses, to stand out in your industry? Now Big data, Data Science, Machine Learning, Deep Learning, Artificial Intelligence (AI), Analytics, Python, R, r-stats are the most trending and highly demanding subject in every sector for almost every industry.
Source: HOB Team4293
Really you want to upgrade your skills with the best Data Analytics , Development courses , to standout in your industry? Now Big data, Data Science, Machine Learning, Deep Learning, Artificial Intelligence (AI), Analytics, Python, R, r-stats are the most trending and highly demanding subject in every sector for almost every industry.
Source: HOB Team17394
Healthcare outpaced all other industries in job growth for freelancers while finishing second to staffing when it comes to non-freelancers.
Source: Health Care IT News9858
Artificial intelligence and big data have formed a truly symbiotic relationship, and they need each other to ring to fruition what both are promising. If there are any lingering doubts that the fates of artificial intelligence and big data are intertwined, consider these recent quotes from two highly regarded thought leaders in this space:
Source: RTInsights2187
Artificial intelligence and big data have formed a truly symbiotic relationship, and they need each other to ring to fruition what both are promising. If there are any lingering doubts that the fates of artificial intelligence and big data are intertwined, consider these recent quotes from two highly regarded thought leaders in this space:
Source: RTInsights7185
Artificial intelligence is starting to impact nearly every aspect of our daily lives. Machine-learning algorithms, the technology behind contemporary AI, determine what content appears on our Facebook feed and what results are returned when we conduct a Google search. They power product recommendations on Amazon and Netflix, determine airline or event ticket pricing, and influence who receives marketing communications based on likelihood to buy a new product or cancel a service.
Source: Maclean's4443
In the tech industry, new skills and roles emerge faster than traditional education can keep up with. A recent example is the field of data science and the associated profession, Data Scientist.
Source: Codementor41676
Artificial intelligence (AI) and its subset, cognitive computing, have been subject to a fair share of debates, with concerns around machines overtaking, or maybe even replacing, the human workforce.
Source: Forbes6909
Accenture hosted an AI, Data Science & Big Data Open House at The Dock to showcase the data and analytics work it does, and open up a discussion about the challenges it faces in finding data-driven solutions.
Source: Silicon Republic4020
Consultants who partner with data scientists can use the power of big data to help sell their expert advice. Find out pitfalls to avoid in this partnership.
Source: Tech Republic7953
The incredible breakthroughs we saw in 2017 for deep learning will carry over in a very powerful way in 2018.
Source: venturebeat5175
Like other prominent AI researchers, the Nvidia team believes the techniques that drive this project will continue to improve in the months and years to come, generating significantly larger and more complex images.
Source: economictimes.indiatimes.com2343
Like other prominent AI researchers, the Nvidia team believes the techniques that drive this project will continue to improve in the months and years to come, generating significantly larger and more complex images.
Source: ET5166
A new article in Science talks about the impact of machine learning advancements on labor demands and the economy.
Source: newsclick6189
How diverse will a lucrative, growing field like data science be in the future?
Source: Forbes8139
Is data science too easy? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.
Source: Forbes5226
The answer to this question depends to a great extent on the role/industry/company combination. However, there are few general remarks that can be made. To start with, it is very important to complete an internship rather than do an "ML related summer research project" unless that research is done with respect to a lab at a university
Source: HOB5865
Machine Learning Engineers, Data Scientists, and Big Data Engineers rank among the top emerging jobs on LinkedIn. Data scientist roles have grown over 650% since 2012.
Source: Enterprise Irregulars4203
Machine Learning Engineers, Data Scientists, and Big Data Engineers rank among the top emerging jobs on LinkedIn.
Source: Linkedin Blog9405
"Han the Robot" waits on stage before a discussion about the future of humanity in a demonstration of artificial intelligence at the RISE Technology Conference in Hong Kong on July 12, 2017. A new simulation of advanced AI reveals what society might look like if a superintelligence is introduced.
Source: Newsweek5163
As AI makes more resources more widely available, we will find less meaning in material wealth and more value in the activities that are uniquely human.
Source: Edweek2937
A start-up specialising in business-to-business payments is to open a development centre in Glasgow, creating 37 data science jobs in the process.
Source: Scotman4707
Bennett Borden, chief data scientist at the Philadelphia firm of Drinker, Biddle & Reath, discusses his take on the evolution of legal analytics.
Source: Law.com3291
The program is the first-of-its-kind that offers industry-recognized certification in Management Program in Data Visualization and Executive Program in Big Data and Machine Learning.
Source: Aninews4041
Over the next decade, artificial intelligence will have a profound impact on all industries, introducing efficiencies and innovative catalysts.
Source: Morningstar2994
Imaging analytics backed by machine learning can accurately predict renal survival time in patients with chronic kidney disease.
Source: Healthitanalytics4389
Artificial intelligence and machine learning are eating up workloads at IT help desks, in cybersecurity, and other IT tasks, stirring significant concern over the long-term impact AI will have on jobs even in the IT industry.
Source: Itworld4539
Data protection platforms are a key element of data supply chains.Yet data supply chains present unique challenges.
Source: Forbes6549
Anyone who is plugged into the tech world knows that AI and big data is big business right now. Our technological ability to process and analyze large troves of data grows every year, unlocking new doors at every turn.
Source: Forbes7884
Results from the Kaggle State of Data Science and Machine Learning survey of data professionals revealed that job satisfaction varies widely across job titles. Data professionals who reported the highest level of job satisfaction were: 1) Machine Learning Engineers, 2) Data Scientists and 3) Predictive Modeler. Data professionals who reported the lowest level of job satisfaction were: 1) Engineers, 2) DBA/Database Engineers and 3) Programmers.
Source: Customerthink13305
It's been a decade since D.J. Patil, LinkedIn's former head of data products, coined the term "data science." And already there are thousands of data scientists working in different companies.
Source: Techgenix12333
Interviews are scary as shit. You sit across the table from someone who has the power to grant you income and measure of security. They hold your future in their hands. You have to make them like you, trust you, think you are smart.
Source: Github.io11571
It is a question that perplexes many an upcoming research student - which IIT is best suited for machine learning and data science research. Globally and on home turf, IITs are recognized as Tier-1 engineering institutions that produce a steady stream of talent in computer science, software engineering, Database and Information Systems and other related domains.
Source: HOB16521
Artificial Intelligence (AI) should be used to solve local problems with the help of global technology, said IT minister KT Rama Rao. The minister, who headed a delegation at the World Economic Forum (WEF) 2018, spoke at a session on "Global Tech and Local Solutions: Artificial Intelligence" in Davos on Friday.
Source: TOI15177
The biggest event on the data science community calendar is the one that showcases women in the field.
Source: Forbes3570
A recent survey of over 16,000 data professionals showed that the most used platforms/resources included Kaggle, Online courses and Stack Overflow Q&A.
Source: Businessoverbroadway13992
University of Michigan-Ann Arbor, University of London, University of Illinois-Urbana Champaign, Imperial College London, and Arizona State University partner with Coursera to build online degrees of the future
Source: Business Wire14031
Coders and job aspirants alike are making a beeline to data science training shops in Bengaluru and Hyderabad, and to open online courses, in the hopes of updating their skills and landing jobs with comfortable salaries. But is the training enough?
Source: Livemint3267
Based on historical data and accurately predicting some patterns out of it then, Data science comes into the picture. Data Science is the data driven decision making and building business strategies based on data analysis by removing any manual or judgemental error. Data Science is everywhere and here is the rescue for how to be a data scientist.
Source: HOB13878
Data science is one of the most lucrative fields to work in today. Learn the basics and get a fatter paycheck with this machine learning class.
Source: Dailydot7410
We live in a world with unprecedented amounts of stats, facts, and figures, and it's slightly overwhelming. And in order to make that data useful, companies need to hire analysts who know how to sift through it and find meaningful patterns. According to GlassDoor, a typical data scientist earns about $120,000 per year, meaning this is the kind of career that can get you living that good life.
Source: Mashable7371
Release 5.1 of Anaconda, the data science and machine learning platform, now includes Visual Studio Code as an IDE. This is part of a wider collaborative effort between Anaconda Inc. and Microsoft.
Source: Infoq7002
Preparing for an interview is not easy - naturally there is a large amount of uncertainty regarding the data science interview questions you will be asked. No matter how much work experience or technical skill you have, an interviewer can throw you off with a set of questions that you didn't expect. For a data science interview, an interviewer will ask questions spanning a wide range of topics, requiring strong technical knowledge and communication skills from the part of the interviewee. Your statistics, programming, and data modeling skills will be put to the test through a variety of questions and question styles - intentionally designed to keep you on your feet and force you to demonstrate how you operate under pressure. Preparation is a major key to success when in pursuit of a career in data science.
Source: Springboard23481
It's undeniable-data science is one of the fastest growing fields in the world today, and shows no signs of slowing down. Because of that, it's becoming increasingly important to study and understand the professionals who make up this field, and the ways they navigate it.
Source: Springboard23244
LinkedIn's 2017 U.S. Emerging Jobs Report-fittingly created with the power of data science-lists data science roles as one of the top emerging positions in the U.S. today, with 6.5X growth over the last five years.
Source: Springborad5142
Cracking any interview requires preparation and in the case of data science it is not restricted to performing well on the big day alone. An aspiring data scientist is expected to prepare across multiple fronts. Here, we provide you with a insight into the levels of preparation required and how to go about it.
Source: HOB9279
It's as good a time as any to keep yourself updated - especially for those who are in the ever-changing technology field. If you're interested in, or working as a professional in Data Science, Machine Learning and allied fields, we've compiled a list of top 11 books that are available free that you must catch up on gloomy rainy days.
Source: HOB14643
Data science requires the effective application of skills in a variety of machine learning areas and techniques. A recent survey by Kaggle, however, revealed that a limited number of data professionals possess competency in advanced machine learning skills.
Source: Businessover broadway15564
In a joint initiative with Google and Udacity, Bertelsmann, the international media, services and education company, is inviting the people 18 and older to apply for its "Udacity Data Science Scholarship Program," in which the company will provide 15,000 three-month Udacity online courses in descriptive statistics.
Source: HOB14805
Top machine learning writers on Quora give their advice on learning machine learning, including specific resources, quotes, and personal insights, along with some extra nuggets of information.
Source: kdnuggets.33651
Here is a great collection of eBooks written on the topics of Data Science, Business Analytics, Data Mining, Big Data, Machine Learning, Algorithms, Data Science Tools, and Programming Languages for Data Science
Source: Kdnugget36948
Machine Learning, The New Frontier In Data Science The ability to draw insight from massive streams of data is becoming a competitive differentiator for enterprises. Gartner evaluated software vendors offering products that allow development and deployment of the data science workloads that deliver that insight.
Source: CRN6690
Are you a Data Scientist looking for a Job? Are you a Recruiter looking for a Data Scientist? If you answered yes or NO to this questions you need to read this.
Source: Kdnugget7656
Nothing takes the place of meaningful and substantive study, but these cheat sheets (that's really not a great term for them) are a handy reference in a pinch or for reinforcing particular ideas. All images link back to the cheat sheets in their original locations.
Source: Kdnugget15450
What better way to enjoy this spring weather than with some free machine learning and data science ebooks? Right? Right? Here is a quick collection of such books to start your fair weather study off on the right foot. The list begins with a base of statistics, moves on to machine learning foundations, progresses to a few bigger picture titles, has a quick look at an advanced topic or 2, and ends off with something that brings it all together. A mix of classic and contemporary titles, hopefully you find something new (to you) and of interest here.
Source: Kdnugget27495
For your convenience, we have prepared a comprehensive overview of the most important libraries used to perform machine learning and Data Science tasks in Scala.
Source: Kdnugget6954
Are you looking to get a real handle on the career paths available in "Data Science" and "Big Data?" Read this article for insight on where to look to sharpen the required entry-level skills.
Source: Kdnugget9594
Strong math understanding, computing skills, critical thinking and presentations skills provide a strong foundation for a career in Data Science.
Source: Kdnugget2838
For the 2018 international women's day, we profile 18 inspiring women who lead the field in AI, Analytics, Big Data , Data science, and Machine Learning areas.
Source: Kdnugget10533
The best jobs right now in the planet include titles like data scientist, data engineer, and business analyst. Yet too often, employers find it hard to acquire the right person for a job. There is a persisting gap between the skills possessed by the current or the emerging workers and the abilities required by the business.
Source: HOB13197
We are now at 91 questions. We've also added 50 new ones here, and started to provide answers to these questions here. These are mostly open-ended questions, to assess the technical horizontal knowledge of a senior candidate for a rather high level position, e.g. director.
Source: DSC17769
Data has emerged as the new oil. Enterprise success now hinges on the ability to extract insights from the unprecedented flow of data. This is where data science serves its purpose to help enterprises see meaning out of information and make strategic decisions.
Source: Marutitech7326
The cabinet of Israel on Sunday approved a $264.5 mn nationwide program, which will span over five years to make health data about its population accessible to private companies and researchers.
Source: HOB7899
This was the subject of a popular discussion recently posted on Quora: 20 questions to detect a fake data scientist. We asked our own data scientist, and he came up with a very different set of questions: compare his answer (#1 below - 20 questions) with Quora replies (#2 and #3 below - 30 questions). Note that #2 focuses on statistics, and #3 on architecture. The link to the original Quora discussion is also provided in this article. Which questions would you add or remove?
Source: DSC16017
There's been a lot of hype about Data Science... and probably just as much confusion about it.
Source: Kdnugget21855
IBM has showcased its new cloud offering called Cloud Private Data that has been designed to assist businesses make use of ML and data science techniques.
Source: HOB7842
We examined 140 frameworks and distributed programing packages and came up with a list of top 20 distributed computing packages useful for Data Science, based on a combination of Github, Stack Overflow, and Google results.
Source: Kdnugget8331
ARE ALGORITHMS taking over our jobs? Yes, yes they are... and that a good thing. With a focus on leveraging algorithms and balancing human and AI capital, here are the top 10 algorithm categories used to implement A.I., Big Data, and Data Science.
Source: Bizcatalyst3605421
Infosys has made an investment of $1.5 mn in Waterline data science, a provider of data discovery and data governance software.
Source: HOB3225
Hone yourself to be the ideal candidate at your next data scientist job interview with these frequently asked data science interview questions. Data Scientist interview questions asked at a job interview can fall into one of the following categories -
Source: Dezyre26799
Data Science has become an integral part of making crucial business decisions in today's competitive market. This is one of the reasons companies are on a rampage to hire Data Scientists and qualified ones at that. The data science job interviews at companies like Facebook, Google, LinkedIn, AirBnB, Insight, Twitter, Mu Sigma have one thing in common - these interviews are tough. But we have a list of helpful data science interview questions from these companies that will help while someone is preparing to apply for the post of a Data Scientist.
Source: HOB56856
The cabinet of Israel on Sunday approved a $264.5 mn nationwide program, which will span over five years to make health data about its population accessible to private companies and researchers.
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Python's growing adoption in data science has pitched it as a competitor to R programming language. With its various libraries maturing over time to suit all data science needs, a lot of people are shifting towards Python from R. This might seem like the logical scenario. But R would still come out as the popular choice for data scientists. People are shifting towards Python but not as many as to disregard R altogether. We have highlighted the pros and cons of both these languages used in Data Science in our Python vs R article. It can be seen that many data scientists learn both languages Python and R to counter the limitations of either language. Being prepared with both languages will help in data science job interviews.
Source: HOB9672
If you are looking to learn python than what could be a better source than taking help from books written by professionals? In order to help you with your search we have created a list of best book for python data science, so that you don't have to wait and based on your requirements you can start your learning process with best books to learn python:
Source: Digital Vidya19545
These articles have been divided into 3 parts which focus on each topic wise distribution of interview questions. Below are some of the questions that maybe asked during a data science interview, that is related to R programing specifically.
Source: Dezyre8583
We will see real-time big data come to the forefront in the enterprise world this year. There is a convergence of several factors that will lead to this. Companies have increasingly begun to use cloud solutions and advanced data processing solutions in order to derive business insights for improving customer experience, optimizing operational processes and providing executives with critical data points.
Source: HOB9615
Here are the four big data trends that will be driving change in the enterprise landscape in the coming year.
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I wrote this quick primer so you don't have to parse all the information out there and instead can learn the things you need to know to quickly get started.
Source: kDnugget10368
Personally, I haven't learnt as much from videos & online tutorials as much I've learnt from books. Until this very moment, my tiny wooden shelf has enough books to keep me busy this winter.
Source: AV9180
A comprehensive course on Hadoop for just $39.
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In this blog, we will discuss Data Science vs Artificial Intelligence vs Machine Learning vs Deep Learning. Also, will discuss each of these individually for better understanding.
Source: Data Flair26469
Based on historical data and accurately predicting some patterns out of it then, Data science comes into the picture. Data Science is the data driven decision making and building business strategies based on data analysis by removing any manual or judgemental error.
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Researchers are working to convert massive sets of big data into unique sound patterns in order to improve anomaly detection and comprehension.
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Natural language processing is a technology that combines big data and artificial intelligence together and brings it to the table.
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Flipkart the indian online retail giant is on a hiring spree and looking for data scientists actively in order to further their AI in India program.
Source: HOB5805
Coming European GDPR directive affects data science practice mainly in 3 areas: limits on data processing and consumer profiling, a "right to an explanation" for automated decision-making, and accountability for bias and discrimination in automated decisions.
Source: Kdnugget5229
The firm's top 10 prognostications on where technology will take us include shopping in AR, corporate fitness programs, and much more.
Source: PC Mag15258
Frustrations of the data scientist! Yes, I am a data scientist and yes, you did read the title correctly, but someone had to say it. We read so many stories about data science being the sexiest job of the 21st century and the attractive sums of money that you can make as a data scientist that it can seem like the absolute dream job.
Source: TDS73395
What I Would Have Told Myself a Few Years ago Two years ago, I shared my experience on doing data science in the industry. The writing was originally meant to be a private reflection for myself to celebrate my two year twitterversary at Twitter, but I instead published it on Medium because I believe it could be very useful for many aspiring data scientists.
Source: Medium12666
Before I get to the meat of this post, I want to make one thing super clear: you do not need a graduate degree to be a data scientist. Unless you're doing cutting-edge machine learning research (which, let's be honest, doesn't describe 99.9% of data scientists including me!), a degree in how to do research just isn't necessary. Anyone who tells you differently is trying to sell you something probably a data science graduate degree.
Source: Freecodecamp10479
I recently came across Rachel Tomas's article on the importance and value of writing about what you learn, and Julia Evans's advice on why and how to write, and thus I have decided to follow their advice and write an article (for the first time ever!).
Source: TDS20625
What Skills Do You Need To Go From Jr. To Sr. Developer. The role of a data scientist still varies from company to company and even team to team. This makes it much harder for companies to create a standardized growth plan for their data scientists.
Source: Hackernoon8817
This is a hard question to answer. Hang with me in this one (and this is not the final answer about the universe, existence and everything.
Source: TDS6843
I recently joined the Enterprise Insight Studio team at Accenture's global centre for innovation in Dublin as an Artificial Intelligence (AI) Software Engineering.
Source: TDS10227
Are Coursera courses still free? At Class Central, I get that question so often that I wrote a guide to answer it.
Source: Freecodemap8784
A great CV might get you an interview. A bad CV will be thrown away!
Source: TDS4797
I've had several conversations recently with people I know in the data science space that always start out about business and then drift to the state of data science as a whole.
Source: DataScience8682
Ability to write a production-level code is one of the sought-after skills for a data scientist role- either posted explicitly or not. For a software engineer turned data scientist this may not sound like a challenging task as they might have already perfected their skill at developing production level codes and deployed into production several times.
Source: TDS6048
The most important lessons I've learned so far... Ok, so it's actually 14 months but it didn't have the same ring to it as "1 year". I've spent that 14 months at one company, News UK. I'm now about to embark on a new journey at Deliveroo as a consumer and growth algorithms data scientist, so I thought now would be a good time to reflect on the things that I've learned during my time at News UK.
Source: TDS7722
A new report aims to help universities shape data analytics education. Technologies that collect data for analysis exist in pretty much every aspect of life - from smart thermometers in homes to wireless sensor networks.
Source: EdTech4617
We discuss 8 ways to perform simple linear regression in Python ecosystem. We gloss over their pros and cons, and show their relative computational complexity measure.
Source: Freecodemap6036
With data now easier to collect and analyze than ever before, companies are recognizing the business value of such information - and the need to tap into it quickly. Enter the chief data officer (CDO), the newest role in the C-suite that is responsible for defining and putting into place a data management strategy.
Source: DataScience5043
I've read a number of articles stating how hard it was to get into Analytics and Data Science. This hasn't been my experience, so I wanted to share. We'll look at interviewing, the tools I currently use, what parts of industry I wasn't prepared for in school, and what my career trajectory has looked like. But not in that particular order.
Source: TDS6513
Based on historical data and accurately predicting some patterns out of it then, Data science comes into the picture. Data Science is the data driven decision making and building business strategies based on data analysis by removing any manual or judgemental error. Data Science is everywhere and here is the rescue for how to be a data scientist.
Source: HOB3390
Data Science is quite a large and diverse field. As a result, it is really difficult to be a jack of all trades. Traditionally, Data Science would focus on mathematics, computer science and domain expertise.
Source: TDS12837
Are you currently pursuing your masters in Data Science? Overwhelmed with Buzzwords and Information? Don't know where and how to start your study? Then start with this article and a starter kit provided, but learn it for excellence and not just for the exams.
Source: Kdnugget7107
In the world of postmodernism, Relativism has been, in its various guises, both one of the most popular and most reviled philosophical doctrines. According to Relativism, there is no universal and objective truth; rather each point of view has its own truth. You must be wondering why I am discussing it and how it is even related to Data Science.
Source: TDS12231
For a myriad of data scientists, linear regression is the starting point of many statistical modeling and predictive analysis projects. The importance of fitting, both accurately and quickly, a linear model to a large data set cannot be overstated.
Source: TDS5211
I followed the latest trend also downloaded the zip archive of my Facebook data, but what I found after analyzing the data is not the thing I was expecting.
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Don't "do something interesting" with data, AI, and ML-do something human-centered
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Artificial intelligence (AI) is growing every day at a furious rate, and with it, the statistics surrounding the industry and the various industries it's revolutionizing are changing.
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As an organizer for a data science meetup group, I am often asked this question.
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Over the past year, I have had the opportunity to speak with a lot of prospective Data Science bootcamp students sharing my pre and post bootcamp experiences and helping them put in context some of the major factors they need to consider before deciding to attend a Data Science bootcamp.
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A person new to the Data Science field details their salary and the negotiation process.
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A basic grounding in the principles and practices around artificial intelligence (AI), automation and cognitive systems is something which is likely to become increasingly valuable, regardless of your field of business, expertise or profession.
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Artificial Intelligence, Blockchain and Machine Learning globally are considered to be the holy trinity of technologies. Startups, SMEs and large corporations all together are looking at the various use case of these technologies. In a recent report, TMT predictions for 2018, Deloitte identified five key developments that will lead the popularity of machine learning in the future.
Source: HOB3594
If you are learning a new skill, think about HOW you are learning. My plan was to never be a student again. I like learning. I enjoy the process of learning and as a teacher and scientist, I am continuously engaged in this process.
Source: HOB4698
How do Machine Learning algorithms handle such large amount of data in companies (or real-life cases)? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.
Source: HOB5193
I started working at www.comet.ml a few months ago, where we are building a really amazing tool for machine learning engineers. The short of it is that we help track experiments using a single line of code that automagically saves everything to make your model reproducible. You can get great experiment logging and history without being tied to a single platform.
Source: HOB4989
I'm sure everyone who has been following tech industry news knows about "big data" and "AI." Although there is no industry-consistent definition for either term, most people tend to agree that both have been playing more and more important roles lately
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nyone with a background in Physics or Engineering knows to some degree about signal analysis techniques, what these technique are and how they can be used to analyze, model and classify signals.
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I attended IBM's inaugural Think event in Las Vegas last week. This event, IBM's largest (estimated 30,000+ attendees!), focused on making your business smarter and included keynotes and sessions on such topics as artificial intelligence, data science, blockchain, quantum computing and cryptography.
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A recent survey of over 16,000 data professionals showed that the most common challenges to data science included dirty data (36%), lack of data science talent (30%) and lack of management support (27%). Also, data professionals reported experiencing around three challenges in the previous year. A principal component analysis of the 20 challenges studied showed that challenges can be grouped into five categories.
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The practice of data science requires the use of analytics tools, technologies and languages to help data professionals extract insights and value from data. A recent survey by Kaggle revealed that data professionals relied on Python, R and SQL more than other tools in 2017.
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Data scientists work at all levels of the organization. Our survey of data professionals revealed that Director-level data scientists have the highest level of proficiency across many data science skills and work with more of their peers compared to data scientists who are Individual Contributors, Managers or even Executives. Satisfaction with outcome of analytics projects did not differ across job levels.
Source: HOB6267
As digital marketing strategies grow more sophisticated and complex, businesses find themselves wrestling with more data than ever.
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A recent survey of over 16,000 data professionals showed that the most used platforms/resources included Kaggle, Online courses and Stack Overflow Q&A. Additionally, the most useful platforms/resources included Personal Projects, Online courses and Stack Overflow Q&A.
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Data science requires the effective application of skills in a variety of machine learning areas and techniques. A recent survey by Kaggle, however, revealed that a limited number of data professionals possess competency in advanced machine learning skills. About half of data professionals said they were competent in supervised machine learning (49%) and logistic regression (53%).
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I still learn new knowledge everyday with my growing passion in Data Science field. To pursue different career track as a graduating physics student there must be 'Why' and 'How' questions to be answered.
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Student demand for degrees in the subject soars as employers seek skilled analysts
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Results from the Kaggle State of Data Science and Machine Learning survey of data professionals revealed that job satisfaction varies widely across job titles. Data professionals who reported the highest level of job satisfaction were: 1) Machine Learning Engineers, 2) Data Scientists and 3) Predictive Modeler. Data professionals who reported the lowest level of job satisfaction were: 1) Engineers, 2) DBA/Database Engineers and 3) Programmers.
Source: HOB10437
It is vital to have a good understanding of the mathematical foundations to be proficient with data science. With that in mind, here are seven books that can help.
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Artificial intelligence is one of the highest demanding fields. It includes general AI, expert systems also known as data mining, machine learning, Neural Network and lastly, fuzzy systems. These have been essential and interesting topics among the students, scholars, faculties as well as professionals.
Source: HOB5289
I recently made a Batman analogy when discussing the topic of data science with some colleagues. In this post, I will explore this analogy further.
Source: HOB7812
In the past few years, I have met up with a lot of employers and conducted interviews for training program. Through the conversations and interviews and seeing the end results, I thought I will share more on how to prepare for your resume and even the interviews for a data science role.
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Using Reinforcement Learning to Tackle CitiBike Rebalancing Problems and Beyond
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Taking decisions based on Data is not only an inherent sense but a strong commercial sense too.
Source: HOB4593
Data science is playing a significant role in managing customer experience. It has contributed to nearly all areas of the CRM. There are still a number of companies, yet to embrace this technology for enhancing their marketing methodologies. One of the main reasons is the lack of awareness of how data science can help engage customers more effectively, and, moreover, an inability to quantify the potential improvements.
Source: HOB2505
NEC Corporation (TSE: 6701) today announced the establishment of dotData, Inc., a new startup company based in Cupertino, California, in the heart of Silicon Valley, that develops and globally provides software that automates data science processes using artificial intelligence (AI).
Source: HOB5055
It seems like data/analytics has much less clarity around roles than most other common functions at tech companies. Do you think this will ever change? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.
Source: HOB3318
Ah the dreaded machine learning interview. You feel like you know everything... until you're tested on it! But it doesn't have to be this way.
Source: HOB15492
Data Science is getting very popular and many people are trying to jump into the bandwagon, and this is GREAT. But many assume that data science, machine learning, plug any other buzzword here, is to plug data to some Sckit-Learn libraries. Here is what the actual job is.
Source: HOB13356
I participated in Santander Customer Satisfaction challenge, ran on Kaggle for 2 months and got into top 1%. Here, I would be discussing my approach to this problem.
Source: HOB7776
I started my way in the Data Science world a few years back. I was a Software Engineer back then and I started to learn online first (before starting my Master's degree).
Source: HOB5529
This is a story about the danger of interpreting your machine learning model incorrectly, and the value of interpreting it correctly. If you have found the robust accuracy of ensemble tree models such as gradient boosting machines or random forests attractive, but also need to interpret them, then I hope you find this informative and helpful.
Source: HOB7242
Most people don't realize, but the actual "fancy" machine learning algorithm is like the last mile of the marathon. There is so much that must be done before you get there!
Source: HOB4875
There are so many amazing ways artificial intelligence and machine learning are used behind the scenes to impact our everyday lives and inform business decisions and optimize operations for some of the world's leading companies. Here are 27 amazing practical examples of AI and machine learning.
Source: HOB21054
Becoming data scientist is really hard. Each & every project requires a different kind of programming language or software to focus on. There is an immense list of tools for data science. Here are top 8 data science tools in 2018:
Source: HOB4350
Data Science is a central part of virtually everything from business administration to running local and national governments. At its core, the subject aims at harvesting and managing data so organizations can run smoothly
Source: HOB6087
Data is everywhere. In fact, the amount of digital data that exists is growing at a rapid rate, doubling every two years, and changing the way we live. Data has been a crucial part of our lives.
Source: HOB4923
Recent advances in processing large amounts of data have generated a plethora of new opportunities to improve individual lives and the welfare of our societies. For example, smart meters monitoring domestic electricity consumption can help save electricity when not at home or suggest the cheapest electricity supplier depending on the consumption pattern.
Source: HOB3018
We are in the midst of a gold rush in AI. But who will reap the economic benefits? The mass of startups who are all gold panning? The corporates who have massive gold mining operations? The technology giants who are supplying the picks and shovels? And which nations have the richest seams of gold?
Source: HOB5352
Data is gold, The amount of digital data in the universe is growing at an exponential rate, doubling every two years, and changing how we live in the world. Big Data is surely a big deal. Data has replaced oil as the world's most valuable resource. Data can help us achieve tremendous things on both the levels ie individual and businesses, and as a society. But to extract the best value from data, you need to be using the best techniques and the best technology
Source: HOB4116
Data science has created so much hype in the world of IT sectors that from big to small companies all are now hiring employees who have knowledge regarding this subject. The data science industry's job market is hot today.
Source: HOB2688
Check out this collection of 9 (plus some additional freebies) must-have skills for becoming a data scientist.
Source: HOB6321
From data driven strategies to decision making, the true worth of Big Data has been realized, and has led to opening up of amazing career choices. Check out these 12 interesting careers to explore in Big Data.
Source: HOB7527
Artificial intelligence (AI) and machine learning are transforming the global economy, and companies that are quick to adopt these technologies will take $1.2 trillion from those who don't.
Source: HOB6552
Google unveiled an AI that can make reservations over the phone. Has the Turing Test been finally passed?
Source: HOB6219
Not everyone who can talk about "entropy loss" has the engineering skills to back it up. And not every hiring manager knows the difference between clickers and coders.
Source: HOB4536
In this feature, we take a look inside the working lives of people whose job titles often warrant the question: 'but what do you actually do?' This week, we speak to Glenn Bunker, data scientist at realestate.com.au.
Source: HOB4914
Part four of my ongoing series about building a data science discipline at a startup. You can find links to all of the posts in the introduction.
Source: HOB5256
Scientists are paid the big bucks for a reason, and that's because a lot of people don't understand what the heck it is we do. But that's why writing is important. It helps us to understand what we do, and explain it to others so they can understand it, too.
Source: HOB3984
Machine Learning (ML) has become massively popular over the last several years. And why... well simply because it works! The latest research has achieved record breaking results, even surpassing human performance on some tasks.
Source: HOB3363
Data Science Congress 2018, an initiative by Aegis School of Data Science and mUni Campus concluded with a bigger bang this year with 2000+ delegates and 100 speakers across industries. DSC 2018 was inaugurated by Shri Vijay Goel, Minister of State for Parliamentary Affairs and Statistics and Programme Implementation, Govt. of India.
Source: HOB5226
It also brings out the fact that India currently contributes about 10% of the open job openings for data scientists globally, making it the largest data science hub in the world outside the U.S.
Source: HOB4617
Convolution neural networks (CNNs) are a family of deep networks that can exploit the spatial structure of data (e.g. images) to learn about the data, so that the algorithm can output something useful.
Source: HOB4095
Not that long ago, the concept of "Big Data" was pretty abstract. Few companies considered it feasible to sift through huge sets of data looking for speculative insights.
Source: HOB4968
Establishing trust in data is an essential requirement for businesses and entities for whom credible, reliable information is the lifeblood. As enterprises seek to manage data as an asset, it becomes increasingly vital that data sources are trusted and verifiable.
Source: HOB4542
TransUnion, the Chicago-based credit reporting agency, has funded the creation of a new professor position at the University of Illinois at Chicago in hopes of addressing a growing need for experts in the rapidly expanding field of data science.
Source: HOB1557
Unlike other projects in the organization, AI data-driven products are new for most of the organizations and the best way to go from research to production. Data science has created so much hype in the world of IT sectors that from big to small companies all are now hiring employees who have knowledge regarding this subject. The data science industry's job market is hot today
Source: HOB2277
Scalable Deep Learning services are contingent on several constraints. Depending on your target application, you may require low latency, enhanced security or long-term cost effectiveness. Hosting your Deep Learning model on the cloud may not be the best solution in such cases.
Source: HOB2619
Data science has created so much hype in the world of IT sectors that from big to small companies all are now hiring employees who have knowledge regarding this subject. Data science is helpful for the employees to get understand about data and then make it in a proper way so that it can be communicated in a better way which is valuable for the companies.
Source: HOB4323
Numbers don't lie data analytics is on rise soon it will be integrate part of all the organizations. Data science has created so much hype in the world of IT sectors that from big to small companies all are now hiring employees who have knowledge regarding this subject. Data science helps an employee to understand data and then synthesize it in a proper way so that they can communicate in a better way which is beneficial for the companies
Source: HOB4128
Data is everywhere. In fact, the amount of digital data that exists is growing at a rapid rate, doubling every two years, and changing the way we live. Data science and data analytics, people working in the tech field or other related industries probably hear these terms all the time, often interchangeably. However, although they may sound similar, the terms are often quite different and have differing implications for business. Knowing how to use the terms correctly can have a large impact on how a business is run, especially as the amount of available data grows and becomes a greater part of our everyday lives.
Source: HOB10059
Machine Learning has become increasingly important today because of the digital transformation of companies leading to the production of massive data of different forms and types, at an ever increasing rate. Due to the advancements in computing technologies and exposure to huge amounts of data, the applicability of machine learning is dramatically increasing.
Source: HOB1530
The basic task of the data science platform is to find and analyze the work that was done in the past, making the job of the data scientists easier.
Source: Zion Market Research4077
A portfolio of real-world projects is the best way to break into data science. This article highlights the 5 types of projects that will help land you a job and improve your career.
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In a perfect world, data scientists would take subjectivity out of their conclusions when examining findings.
Source: HOB3123
Last Earnings, Twitter Inc. soared the most since its market debut in 2013 after it posted the first revenue growth in four quarters, driven by improvements to its app and added video content that are persuading advertisers to boost spending on the social network - Bloomberg
Source: HOB2853
In our last post, we started using Data Science for Credit Risk Modeling by analyzing loan data from Lending Club.
Source: HOB4599
A guide to making the most out of your data.
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Having done training and mentoring for quite a while, I noticed something that is not taught in most data science curriculum that I have come across but in my opinion, its an essential business knowledge that the data scientist need.
Source: HOB3237
Data science has created so much hype in the world of IT sectors that from big to small companies all are now hiring employees who have knowledge regarding this subject. Data science helps an employee to understand data and then synthesize it in a proper way so that they can communicate in a better way which is beneficial for the companies. Data Science is now know as the sexiest job of the 21st century.
Source: HOB2757
In order for data scientists to be effective at a startup, they need to be able to build services that other teams can use, or that products can use directly.
Source: HOB2355
Interactivity allows you to embed much more information than in a static visualisation by using tooltips, click-events, ability to filter etc.
Source: HOB3480
AI for Diagnostics, Drug Development, Treatment Personalisation, and Gene Editing
Source: HOB6402
DeepMind and other universities has published many End to End Reinforcement Learning papers that are used for problems that can be solved by a single agent. End to End RL algorithms learns both feature representation and decision making in the network by taking pixels as the input and the controls as output.
Source: HOB8805
Let me start by saying that there is no one way to being a self taught data scientist. You have got to find out what works for you.
Source: HOB6180
Doctors have always written clinical notes about their patientsĆ¢??-Ć¢??originally, the notes were on paper and were locked away in a cabinet. Fortunately for data scientists, doctors now enter their notes in an electronic medical record.
Source: HOB4605
The growth of data is not going to stop. This will usher in new challenges and opportunities. Below you can find the five hottest big data trends for techies and business.
Source: HOB1914
Data Science is on the rise, both from a company's perspective and from an employee's perspective. This makes data science a great field to get into at the moment.
Source: HOB1767
Every company requires different sets of talents, while some jobs require theoretical knowledge; some jobs are based more on your practical knowledge. Same is the case when it comes to getting jobs in data science, getting jobs in data science has it owns unnerving effects. A great portfolio in this case is a good way to showcase your skills what you are good at what your strengths are. This is the best way to show your employers your skills that you have been learning.
Source: HOB720
The ever-improving capabilities of big data platforms increasingly create new opportunities for industries with representatives who want to examine analytics to benefit their companies.
Source: HOB10074
It was declared as the "sexiest job of the 21st century," by Harvard Business Review. While the job has got a great description by Harvard the career path for now is a bit uncertain.
Source: HOB5139
Much of the AI capability working its way into BI tools today isn't entirely new consumer technologies have been successfully implementing them for years. In fact, this is one of the strengths of artificial intelligence when applied to business intelligence the fact that users already understand intuitively how to use products like Google and Amazon making it easier for them to adopt those same technologies and interaction paradigms in BI tools
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Solving a complete machine learning problem for the societal benefit
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In data science, computer science and statistics converge. As data scientists, we use statistical principles to write code such that we can effectively explore the problem at hand.
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Gain some perspective on the Netflix interview process, and on ways to prepare for just such an industry interview.
Source: HOB13218
I wrote my first line of R code in 2010 for a class at the University of Washington (UW). I was hooked once I realized how much more powerful coding is than spreadsheets. Over the past decade, I witnessed the term 'data science' come into widespread use and saw the rise and fall of buzzwords like big data, business intelligence, analytics, and now artificial intelligence.
Source: HOB117570
Getting the most from our model, figuring out what it all means, and experimenting with new techniques
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Data science interviews are notoriously complex, but most of what they throw at you will fall into one of these categories.
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Sometimes you open a big Dataset with Python's Pandas, try to get a few metrics, and the whole thing just freezes horribly.
Source: HOB4221
I would like to live in a world whose systems are build on rigorous, reliable, verifiable knowledge, and not on alchemy. Simple experiments and simple theorems are the building blocks that help understand complicated larger phenomena.
Source: HOB10773
Interviewing is a skill. Here are 10 tips and resources to improve your Data Science interviews.
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Check out part 2 of this excellent series of articles on becoming a data scientist, written by someone who spends their day recruiting data scientists. This installation focuses on learning.
Source: HOB4716
We examine what's important for data scientists in their careers, including challenging work, networking with peers, foreseeing their career path and creating a good work-life balance.
Source: HOB1590
When I heard about the work at UNDP Global Pulse, I thought it was something straight out of a movie. Data science for social impact sounds like the coolesting thing I can do with mathematics.
Source: HOB31890
It has been a while even since I posted on Medium. Having been in Data Science for almost half a year, I've made a lot of mistakes and learned from the mistakes along the wayā?¦ through the hard way.
Source: HOB3885
We asked our LinkedIn group members what their greatest challenges were to becoming fully fledged data scientists. Some of the most common frustrations were:
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As someone who has been there, I'd like to outline a few practical ideas to help junior data scientists get started at a small software company. The steps were drawn from my personal journey and that of others before me.
Source: HOB2223
Data Science, Machine Learning, Artificial Intelligence and data analytics are quite buzzword. No doubt these technologies will transform all the industries but most likely the technology that will change our profession in the short run will be Robotic Process Automation (RPA).
Source: HOB510
Data Science is quite a large and diverse field. As a result, it is really difficult to be a jack of all trades. Traditionally, Data Science would focus on mathematics, computer science and domain expertise.
Source: HOB8691
Deep Learning is one of the hottest technologies out there. There are many research papers in Deep Learning, and it can be really overwhelming to keep up.
Source: HOB3336
How do you think data science will change over the next 10 years? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.
Source: HOB2412
Useful tips to get started writing about your data science projects
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I was listening to an old episode of Partially Derivative, a podcast on data science and the news. One of the hosts mentioned that we're now living in the "golden age of data science instruction" and learning materials. I couldn't agree more with this statement. Each month, most publishers seem to have another book on the subject and people are writing exciting blog posts about what they're learning and doing.
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This curated list of mindset-changing books will help you become a better Data Scientist
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A carefully-curated list of 5 free ebooks to help you better understand the various aspects of what machine learning, and skills necessary for a career in the field.
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I hope Part 1 sold you on the idea that version control is a critical tool for managing data science experiments. But the devil is in the details, so let's talk about how to implement version control in a data science project.
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What You Need to Know about Machine Learning. This eBook offers you the perfect place to lay the foundation for your work in the world of Machine Learning, providing the basic understanding, knowledge, and skills that you can build on with experience and time.
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Nowadays, there is a huge list of powerful data visualization tools to help you illustrate your ideas, visualize your data, make it talk, share your significant analytics with customers and the global community.
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I recently had the chance to use machine learning to address an issue that is at the forefront of the American media, the difficulty of recognizing fake news.
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Harvard Business Review has regarded data scientist as the sexiest job of the 21stcentury. In this article, with the assistance of Octoparse V7, one of the best free web data scraping tool, we aggregated the resources and tools that you may need to become a data scientist.
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Machine Learning opportunities can be sparse, so when you finally get invited to that long-awaited Machine Learning Interview, you want it to go perfectly. Let me show you how.
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The essential mathematics necessary for Data Science can be acquired with these 15 MOOCs, with a strong emphasis on applied algebra & statistics.
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Actionable takeaways from a memorable experience As we moved into August and summer begins to wind down, I thought I'd take the time to reflect on my last 12 weeks as a Data Science Intern for Unity Technologies in San Francisco, CA.
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At the moment of writing this post about Data Analytics and Data Science, I am bootstrapping a data literacy consultancy, catering to large enterprises around the globe.
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Learn about the various options you have to setup a data science environment with Python, R, Git, and Unix Shell on your local computer.
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Did ATMs wipe out the bank tellers? No. Did PDFs wipe out the print industry? No. Did self-service checkout wipe out cashiers? Still no. Still, many jobs are changing thanks to the onslaught of automation and AI, resulting in types of new roles and responsibilities.
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Machine learning is an application of artificial intelligence that gives a system an ability to automatically learn and improve from experiences without being explicitly programmed. In this article, we have listed some of the best free machine learning books that you should consider going through (no order in particular).
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Completing your first project is a major milestone on the road to becoming a data scientist. It's also an intimidating process. The first step is to find an appropriate, interesting data set. You should decide how large and how messy a data set you want to work with; while cleaning data is an integral part of data science, you may want to start with a clean data set for your first project so that you can focus on the analysis rather than on cleaning the data.
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Here details of the top 9 data science skills that potential data scientists must have to be competitive in this growing marketplace from the perspective of a recruiter.
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It's often said that data is the new world currency, and the web is the exchange bureau through which it's traded. As consumers, we're positively swimming in data; it's everywhere from labels on food packaging design to World Health Organisation reports.
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The connected devices (The Internet of Things) generate more than 2.5 quintillion bytes of data daily. All this data will significantly impact business processes and the Data Science for IoT will take increasingly central role.
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Preparing for an interview is not easy - naturally, there is a large amount of uncertainty regarding the data science interview questions you will be asked. No matter how much work experience or technical skill you have, an interviewer can throw you off with a set of questions that you didn't expect.
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I came across a challenge on Kaggle called PASSNYC: Data Science for Good. Nelson Mandela was right. Education is a powerful weapon as well as one of life's greatest gifts.
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Data Science is very hot and demanding field which contains methods and techniques from the other fields like statistics, machine learning, artificial intelligence, Bayesian and many more other fields. The main purpose of these fields is to generate meaningful insights from the collected data.
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Data visualization is an art which converts numbers into effective knowledge. There are a few programmes out there to help you in data visualization, one of the programmes that help you learn this art is R Programming.
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A portfolio of real-world projects is the best way to break into data science. This article highlights the 5 types of projects that will help land you a job and improve your career.
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Like other careers that don't come without challenges; data science too has its own challenges to concur.
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Crunchbase lists over 5,000 startups who are relying on machine learning for their main and ancillary applications, products and services today.
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Modern data science emerged in tech, from optimizing Google search rankings and LinkedIn recommendations to influencing the headlines Buzzfeed editors run. But it's poised to transform all sectors, from retail, telecommunications, and agriculture to health, trucking, and the penal system.
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Despite the struggles, it is possible to leverage data science and machine learning to scale your business, save time and grow revenue while improving your customers' experience.
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Six months ago I quit my job as a junior JavaScript developer and traveled around south-east Asia for five months. Within a week of getting back to the UK, I had three job offers and had accepted an offer for almost double my previous salary. It wasn't easy, but it was worth it. Here's how I did it.
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In this article you will read about 15 Android applications which can be useful for a data scientist or data analyst.
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Data scientists are the MVPs of any IoT program, but difficulties preparing and leveraging data threaten how quickly they can deliver. Knowing what's lurking in the shadows can streamline the most difficult processes.
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Tech giant IBM on Wednesday announced a partnership with IIT Bombay to advance artificial intelligence (AI) research in India.
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Data Science is becoming an integral part of business systems in the modern world primarily because of the increasing dependence on technology.
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As data science and big data get the hype in the industry, handling it is a challenge we need to deal with. Along with all the pros on one side keeping yourself advent with the latest improvements in this field is another issue which bothers us.
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The popularity of data science, big data jobs in India and globally has leapfrogged over the past five years or so. Its successful run in the industry can be attributed to better research, project implementations and the general growth in big data and data science. These developments have called out for techies trying to make a career in data science.
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I want to explore the real challenges of data science, based on perspectives from those in the field and those who manage them. However, no career is without its challenges, and data science is not an exception.
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This article list data sets from the data science world that you might find interesting.
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We covered 50 data sets for data scientists that are amusing in part 1. In part two we cover 50 more of those.
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50 data sets that data scientist find amusing.
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Raise your hand if you've been caught in the confusion of differentiating artificial intelligence (AI) vs machine learning (ML) vs deep learning (DL)...
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Here is a great collection of eBooks written on the topics of Data Science, Business Analytics, Data Mining, Big Data, Machine Learning, Algorithms, Data Science Tools, and Programming Languages for Data Science.
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Machine Learning (ML) models are making their way into real-world applications. We all hear news about ML systems for credit scoring, health-care, crime prediction.
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What do data science, data analytics, and business intelligence mean at Grab and how are they being used? - Wong Mun
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This "classic" (but very topical and certainly relevant Big Data) post discusses issues that Big Data can face when it forgets, or ignores applied statistics. As great of a discussion today as it was 2 years ago.
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The Tech Companies are hiring for various positions in India and abroad for Data Science, Artificial Intelligence, Machine Learning. Know the eligibility criteria, job location, and profile. Find out what all is needed to work with the biggest tech-giant in the world
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More free resources and online books by leading authors about data mining, data science, machine learning, predictive analytics, and statistics.
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Demand for data scientists is at an all-time high and will continue to be at record levels in the coming years while these professionals become more scarce.
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Deep learning, artificial intelligence, and neural networks are challenging new concepts for many, but an intensive short course from ICHEC aims to plug the knowledge gap.
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I would never use as a data scientist, or too shallow: not giving me enough information to help me understand how to be effective with Docker quickly.
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Are you a hard-core enthusiast of data visualization? Or a beginner, who wants to learn and be able to create more effective visualizations? Check out our list of 35 invaluable books you must read for better visualization.
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There is considerable hype around data science. Websites and social media are flooded with articles on Big Data, Data Science, and Data Analytics. These fields are projected as top fields, while data scientists are considered as saviors of the world and hence are supposed to be highest paid professionals.
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Data analytics is becoming more vital for businesses, and data scientists are in high demand. But the emerging field is broad, and some companies say they have struggled to find job candidates whose skills fit their needs.
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The world around us is rapidly changing with machines becoming more intelligent. Machines learn from data that we have collected over the years and what we generate each day. Machine learning is not a new concept but was actually coined by Arthur Samuel in the year 1959
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Data scientists has taken the spot of the number one job in America, and not only for America Data Scientists, data science jobs are amongst the most coveted careers all around the globe.
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IBM recently predicted that in the next two years there might be a boost of 28 percent in the number of employed Data scientists.
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Embarking on a journey through the lands of machine learning? Here are few important lessons like Feature Engineering, Model tuning, Overfitting, Ensembling etc. which you should keep in mind along the way.
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With data sciences being the focal point, Entrepreneur India analyses why this new trend is now the essential tool for a majority of smart entrepreneurial solutions.
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Most developers have dubbed Python as the Swiss Army Knife in the data science community. It is easy to understand the reason behind it.
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Data analytics is providing the HR department with new insights into employees and policies in the workplace.
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Machine learning has tremendous potential to transform companies, but in practice it's mostly far more mundane than robot drivers and chefs. Think of it simply as a branch of statistics, designed for a world of big data.
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Here is a non-exhausting list of curious problems that could greatly benefit from data analysis.
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Learn about ten machine learning algorithms that Everyone should know to become a data scientist. Machine learning practitioners have different personalities. While some of them are "I am an expert in X and X can train on any type of data," where X = some algorithm, others are "right tool for the right job" people.
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The average company faces many challenges in getting started with machine learning, including a shortage of data scientists.
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Over the last year, I taught myself data science. I learned from hundreds of online resources and studied 6 - 8 hours every day. All while working for minimum wage at a day-care.
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A data scientist needs to be Critical and always on a lookout for something that misses others......
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In today's world, whatever your job, having skills and knowledge in Data Science will play a huge role in your career development. For example, big data and analytics gathered from customers allow marketers to build more effective digital marketing campaigns.
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Understanding data is key to unlocking job opportunities - Harvard Gazette. New course hopes to give students an edge in the job market.
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Data Scientists are expected to have a broader set of skills, which is realistically not possible. We believe a time will come when we expect more specialisation and collaboration by data scientists, rather than expecting one person to know everything.
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5 years ago the idea of extracting value from data was new to businesses, and that businesses had to be convinced that it was worth their effort to collect data and analyze it for meaningful patterns from which they could benefit.
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Until a few years ago the work of data scientists was isolated and mattered primarily for research and/or R&D purposes. The industry has been extremely thankful for the contributions of these clever individuals but we need them now in the mainstream.
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This curated list of mindset-changing books will help you become a better Data Scientist. According to Drew Conway, the Data Science Unicorn is an expert in statistics, programming, and business.
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A carefully-curated list of 5 free ebooks to help you better understand the various aspects of what machine learning, and skills necessary for a career in the field.
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The 50 companies on the just-released LinkedIn Top Startups list in the U.S. have a whopping 3,069 open jobs, a reflection not only of their ambitions and expansion plans but also an ever-tightening national labor market, with more positions going unfilled.
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There are several ways companies can alleviate the pain and accelerate the data science transition, particularly as it relates to the IT department.
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Ability to write a production-level code is one of the sought-after skills for a data scientist role- either posted explicitly or not. For a software engineer turned data scientist this may not sound like a challenging task as they might have already perfected their skill at developing production level codes and deployed into production several times.
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Ability to write a production-level code is one of the sought-after skills for a data scientist role- either posted explicitly or not. For a software engineer turned data scientist this may not sound like a challenging task as they might have already perfected their skill at developing production level codes and deployed into production several times.
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What are the most to least important skills, and the types of people who apply for data science jobs. I talked about all of the skills I want in an ideal candidate. But since that candidate doesn't exist, I have to prioritize what attributes the candidates that I hire have.
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