There has been a lot of interest in artificial intelligence and predictive learning systems - and with good reason. The systems provide a fast, powerful method to handle data analysis
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There is more data out there than ever before, but organisations should be smart about how they use it.
Source: Gulfnews17205
Scientists crunching numbers on infant deaths in the US are using data-analysis algorithms to try and find new ways to reduce the number of babies lost to SIDS each year, with Microsoft contributing free cloud hosting and software tools for their work.
Source: The Star10059
Think beyond the nosy neighbour to the corporations that want to utilise minutia of your life to sell products that you may or may not need. Corporations have always been interested in understanding consumer behaviour and been collecting data about users using their products or service.
Source: The Hindu9732
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.
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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 Vidya31659
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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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.
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We probably all know that obesity is becoming a big problem in the developed world and just becoming bigger similiarly data analysis is becoming an important part of the businesses growth. Big data is the act of collecting large data sets from traditional and digital sources to identify trends and patterns. It is very necessary to get understand the structured and unstructured data in order to make right decision for the businesses to grow.
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In our last post, we started using Data Science for Credit Risk Modeling by analyzing loan data from Lending Club.
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Industries are now leveraging the chatbots in their daily operating functions thus all the activities are performed by bots with minimum efforts and they can be more focused towards another important task in the organisation. The bots gain the popularity and now they are talk of the town.
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Interactivity allows you to embed much more information than in a static visualisation by using tooltips, click-events, ability to filter etc.
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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.
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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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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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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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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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The artificial intelligence (AI) industry has been leading the headlines consistently, and for good reason. It has already transformed industries across the globe, and companies are racing to understand how to integrate this emerging technology.
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The big data analytics technology is a combination of several techniques and processing methods. What makes them effective is their collective use by enterprises to obtain relevant results for strategic management and implementation.
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Machine Learning is the term which we have been Hearing Now everywhere. When I Started My ML Journey Back in April 2016 I was like complete Noob having No Idea what ML is I used to Think does ML means that Machine are learning ?
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Why Data Analytics? To answer this question, you need first of all few clues about my background. I am Rachid Oukhai, founder of Upsilon, Peculium (Data).
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Big data is used by companies around the world to inform and improve countless business processes, from customer service to marketing campaigns. But the ability to collect and analyze vast amounts of information isn't just useful for external operations; it can help you strengthen your business internally, too.
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Understanding how artificial intelligence (AI) and machine learning (ML) can benefit your business may seem like a daunting task. But there is a myriad of applications for these technologies that you can implement to make your life easier.
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In general explanation, data science is nothing more than using advanced statistical and machine learning techniques to solve various problems using data and Data Analysis. Yet, it's easier to just dive into applying some fancy machine learning algorithms -and Voila! You got the predictionâ??-â??without first understanding the data.
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There are numerous of Big Data tools for data analysis today. Data analysis is the process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision making.
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Despite my math background, I've always considered myself first and foremost a consumer researcher who uses data analytics to gain insights into human behavior, and that's what I focus on at Farmers Insurance. Today, if you're a small business owner, you need to get that data just as much as any large corporation. And even if you've always been math-averse, you can learn how to apply analytics to your own business.
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Youtube is a very popular source to educate and entertain people. To learn Artificial Intelligence, Machine Learning and Data Science youtube proved as a good online source by the users. This is great source for educational videos. Now all these technologies are becoming popular day by day and everyone want to learn and get start their career in these fields so they are searching these video channels on youtube.
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Data Scientists is gaining much attention in the age of analytics at the same point of time the role as a Data Engineers are equally important. Data Scientist filed is evolving and they plays a dual role in the organizations. Data engineers are responsible for the databases, data pipelines, and data services that are prerequisites to data analysis and data science.
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I analyzed the Stack Overflow survey and found a stark contrast in the salaries of software engineers, youth, interest in new tools, opinions about AI, ethics and more...
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According to the August 2018 report by the employment-oriented service, data science skills are rising in demand across industries in the U.S.
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Data is everywhere. It is the most important resource in today's world and every organization is busy in collecting the huge amount of data. 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. According to IBM, 2.5 billion gigabytes (GB) of data was generated every day in 2012.
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Data is everywhere. It is the most important resource in today's world and every organisation is busy in collecting the huge amount of data. 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. According to IBM, 2.5 billion gigabytes (GB) of data was generated every day in 2012.
Source: HOB5358
Data is everywhere. It is the most important resource in today's world and every organisation is busy in collecting the huge amount of data. 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. According to IBM, 2.5 billion gigabytes (GB) of data was generated every day in 2012.
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Once the Business Intelligence reports and dashboards have been prepared and insights which are extracted from them, this information becomes the basis for predicting future values. And the accuracy of these predictions lies in the methods used.
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During my time in freeCodeCamp, I have read many posts and articles from students without previous coding experience who eventually found jobs as software developers.
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R programming language is data analysis software which is used by analysts, quants, statisticians, data scientists, and others.
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With the manifold of data science tools in the market, it is certainly a rising challenge for you as a data scientist or a blooming data scientist to sort out the best ones.
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The art of making data beautiful is taking the world by storm. Data visualization experts and artists are creating amazing things in the world of data design every single day.
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How diverse will a lucrative, growing field like data science be in the future?
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Leadership-capacity constraints are undermining many companies' efforts. New management structures, roles, and divisions of labor can all be part of the solution.
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In this generation, data is increasing with a great speed and data science has become the most accepted discipline of proficiency. Internet serves you with multiple sources of information on many websites. To make a better use of the data, data science started with statistics. To deal with the issues and provides the solution to the problems, at the later parts algorithms were introduced. The age of digital media and computers has started then. Every data was computerized which became a way to develop artificial intelligence and data analysis.
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As technology redefines how work is done, finance leaders are having to rethink what constitutes finance talent. The successful finance workers of the future will need skills that are not commonplace in the function today. What are the emerging roles and skill sets of the future finance function?
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Companies that fail to apply data science will be at a competitive disadvantage, according to Deloitte. Here's how to take advantage of new tools, staffing models, and training strategies.
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The idea of transforming digitally is quite divergent and it has progressed and enlarged up from few years. Earlier, the development is technology was not too much the recent years it has evolved and entered the business lexicon. We use to apply advanced technologies to the process which already existed just to increase the efficiency which is like new tools are used to do the same things. Digital industry has evolved and expanded the IT industry as well. To achieve a competitive edge new tools are used to perform the task differently. New technologies are implemented which helps in the procedure more effectively in the marketplace.
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Now have you ever come across the term data mining? As the name implies, it is an analytic process used to explore a large amount of data in regards to consistent patterns and systematic relationships between variables. Businesses prefer data mining because it aims to predict. Predictive analyses, on the other hand, refine data resources, in particular, to extract hidden value from those newly discovered patterns. �¢??Data mining + Domain knowledge =>Predictive Analytics =>Business Value�¢??
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The amount of data generated these days from all business domains conjointly called massive data is large, encompassing data gathering, data analysis, and data implementation method.
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All professionals I'm sure looking ahead to a new start and want to increase their data analysis skills. So here is the collection of books through which data scientist can sharpen up their knowledge and skills.
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They want to make most of every dollar they spend. Data analysis that helps those small business owners target their customers is an essential element of success, and the quality of that analysis could mean the difference between a profit and a loss.
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Big Data is immense at the moment. From a startup to a healthcare firm, from a big MNC to an agricultural field, Big Data is being used almost everywhere. Therefore, the cope in the world of Big Data is immense. Also, as the Big Data industry is pretty huge, therefore, it may not be easy to grasp complete knowledge of the department together. It can be a little scary to learn every aspect of Big Data as well as the related technologies.
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These days, there are ample of businesses which are started just to know the true potential of gathering and examining the data which is of huge quantity in real time. The cases which are already being discovered the enterprises are becoming proactive with them by leveraging the data of real-time to analyzing the situations of the real-time, predicting the events of future, the process of business is improved by taking the spontaneous actions, regulation is being adhered and the experience of the customer is enhanced.
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Python is the programming language amongst all which is gaining popularity the most. People interest shifted towards Python and all are learning this language. I learned HTML and CSS however, currently, I'm trying to find a language that I will use for more than internet development.
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These are the top 10 machine learning which might lead you towards good skills and vast opportunities for your career. All these languages are the highly rated machine learning repositories.
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The fine must have skills to become a Machine Learning Engineer are explained well here which may benefit you for making your future safe.
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If you're a beginner or experienced as a Data Scientist then you must aware of these data science books. Books are the best source to get insights and increase our knowledge.
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Machine learning is exploding, with smart algorithms being used everywhere from email to smartphone apps to marketing campaigns.
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Check out this collection of six books which tackle the hard skills required to make sense of the changing field known as open data and muse on the ethical implications of a digitally connected world.
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Master Multiple programming languages with different books which will enhance your knowledge and teach you the techniques of Learning programming languages.
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There are many things which are way too difficult to grab, but sometimes getting way to this uncomplicated language of data visualization sorts everything to a concept which you can get.
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Machine learning and Artificial Intelligence abilities are expanding continuously with great heights.
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It seems that these days building a career is a bit dicey task and here you will see how to build a career in machine learning with R programming language.
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Data science, Data mining and Data analysis are abuzz today with the number of jobs growing rapidly with each coming day in these fields.
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To a data science, there is nothing more exciting than the data revealing insights about real organizational issues. However, it is completely deflating to present the insights to management and accomplish nothing.
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Here are some best educational applications which will enhance your learning and benefit is that they can be accessed on Android phones.
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Working as a Data Scientist you will analyze data sets which are more complex and large in number as compared to a Data Analyst job.
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According to Spectrum Survey conducted by IEEE, R ranks 7th among the top 10 Programming Languages of 2018.
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Here are some online courses which will give you more of data science knowledge and help you build a lucrative career.
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You need to have done Data Warehousing before doing Data mining.
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So here you can see some real-life instructors just to make sure that there is a proper effective environment of learning for students there.
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This article will dive through some of the most Frequently Asked questions in Data Science Interviews with the help of a popular video of YouTube so that your preparation for the next Data Science interview becomes easier.
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In Part 1, I have already discussed some of the courses related to Programming, Engineering, Computer science, and social science and courses related to science and personal development are discussed in Part 2 and here rest of the courses are discussed:
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See the major difference between the sub-categories of data science, machine learning, and big data.
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Are you thinking that from where would you learn Python Programming Language? So here are multiple resources to go through.
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As visualizations go hand in hand with analysis and an analyst job also contain the role of making effective visualizations, Data Visualization and Data Analyst are often taken synonymous with each other.
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Some HiTech Engineers or college grads will now pop up and say Coders & Programmers are same but they are NOT.
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Whether you just want to stay informed in the data craze or you're looking to kickstart your data science or data literacy journey, this article features a list of books.
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Many technical skills require training and experience to master. They are also typically a type of hard skill. Hard skills are those that can be taught in a classroom and can be defined, evaluated, and measured.
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In this data-driven world usage of words like Data Analysis, Data Mining, Data Science, Machine Learning, and Big Data are common and are often used by the professionals in the field. Often these terms are confusing to a beginner and the terms seem similar to a novice in the field.
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With the help of Predictive Analytics businesses now predict what ups and down they are going to face in the nearer future. These predictions help a business in taking controlled decisions and thus improves the major business decisions.
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Here you will find multiple websites offering you various courses in data science which have perks of learning and provide online lectures too as per your convenience.
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This bundle helps you dive in, with over 400 video tutorials on machine learning and data science. The lessons show you how to build machine learning algorithms and neural networks, using popular frameworks such as TensorFlow and Keras.
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The Reserve bank of India will promote the use of data analysis to identify cases of fraud and help instant response and recovery actions, such as blocking irregular transactions before payment authorization.
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So here are some Big Data Analytics tools which we will explore in detail in this article.
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Here are some of the data science courses which are provided online globally with online certificates and lectures are provided according to your feasibility.
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If you really want to know the demand of data science, this article will give you a complete check of who is a data scientist and the future jobs of a data scientist with a pay scale in the near future.
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These videos will provide you with a comprehensive and detailed knowledge of Natural Language Processing, popularly known as NLP.
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Some books which will help data scientist to build their career with these famous Data Science courses.
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Machine Learning is invading this world gradually and gradually. If we can develop a driverless car then it is Machine Learning.
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What are some of the most popular data science tools, how do you use them, and what are their features? Here are some specializations which will give you a glimpse of data science study.
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Any firm looking to hire a young data analytics professional would expect them to be aware of the most basic concepts of data querying.
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Data Science has been ranked as one of the hottest professions and the demand for data practitioners is booming.
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Machine learning is the holy grail of data analysis, but unfortunately, that holy grail oftentimes requires a PhD in Computer Science just to get started.
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Data Science Tools, Data Analysis, Data Warehousing, Data Mining, Microsoft Azure, MySQL, DataRobot, Amazon
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We are going to discuss the technologies and innovations that are on the verge of making a difference in society. Here are some technologies that are yet to be widespread but have been showing other signs of being ready to move to the next level.
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A data scientist will be responsible for designing and implementing various processes and different layouts for the intricate and large-scale datasets that are basically used for modeling, data mining, and various research purposes.
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A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges. The goal of data science is to improve decision making through the analysis of data.
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Gain new insights into your data. Learn to apply data science methods and techniques, and acquire analytical skills.
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Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be.
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Machine Learning is in trend these days having smart algorithms which are used at multiple places like emails, smartphones to marketing campaigns.
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Data Science is one of the career paths that we've seen the Bootcamp model successfully applied to over the past couple of years.
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Data science is a present-day technology world using a very common term. It is a multi-disciplinary entity that deals with data in a structured and unstructured manner.
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One of the most misunderstood terms in technology is artificial intelligence. There have been several arguments about how this could result in a very disturbing concept for the human race.
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The information technology sector has some of the most lucrative jobs in the world. According to data from jobs site Indeed, the IT space has been the most consistent in jobs growth over the past five years. Between February 2018-19, there was a 31-percent rise in technology jobs.
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India is on the cusp of innovation and is going all guns blazing to digitize the citizen-centric services. One of the greatest challenges testing this collective vision will be to prudently channelize gains, to refine the standard of living of the poorest of poor.
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Data visualization is the graphic representation of data analysis to achieve clear and effective communication of results and insights.
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Machine learning is exploding, with smart algorithms being used everywhere from email to smartphone apps to marketing campaigns.
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Apart from high-school and boardroom presentations, data visualization is used in a multitude of other places too. Where exactly - do you ask? Let us take a look at some of its major applications.
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The demand for skilled data science practitioners is rapidly growing, and this series prepares you to tackle real-world data analysis challenges.
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Machine learning is one of the fastest-growing areas of computer science, with far-reaching applications.
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Launch Your Career in Data Science. A ten-course introduction to data science developed and taught by leading professors.
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What this simply means is that artificial intelligence can help to improve human life and reduce stress. Here are the benefits of artificial intelligence.
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Data Visualization has become one of the common buzz phrases swirling around the internet these days.
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Data science makes use of a scientific approach to gain insight and knowledge out of data. It employs different processes, systems, and algorithms to derive insights out of structured and structured data.
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It is a rapidly famous term used to describe the exponential growth and availability of both structured and unstructured data. And big data has now turned out to be as important to business - and society - as the Internet has become.
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Data Analysis helps the organizations gain insight into how much progression or regression their performance is exhibiting.
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The real task of a data scientist is to design high performing prediction engines. Prediction engines, in turn, help the company either expand business or increase revenue.
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Data visualization allows for understanding at a glance to allow technical and non-technical team members the same in-depth exploration and explanation of complex data patterns.
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Learn to train and assess models performing common machine learning tasks such as classification and clustering.
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Today the saying 'knowledge is power' fits perfectly for the internet. Tons of data is transferred over wireless connections in the world, but its management can be hectic for an unprofessional.
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You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks.
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By now we have all seen the substantial impact of Big Data in helping organizations enhance their performance by converting raw or unstructured data into insightful data.
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With the great increase of data in this generation, data science has become one of the most accepted disciplines of competence.
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Machine learning is one of the fastest-growing areas of computer science, with far-reaching applications.
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Big data courses play a vital role in your career as they can allow you to be a much more effective contributor to the company's bottom line.
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This specialization is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation.
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As artificial intelligence and technology steps into the world, it is estimated that the USA alone will lose 16% of existing jobs.
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It is no doubt that python is one of the best-suited programming languages when it comes to a data scientist. It has been spoken of time and again that Python is the most common programming language in the case of computing.
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It is a rapidly famous term used to describe the exponential growth and availability of both structured and unstructured data. And big data has now turned out to be as important to business - and society - as the Internet has become.
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Artificial Intelligence (AI) and its subsets Machine Learning (ML) and Deep Learning (DL) are playing a major role in Data Science.
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Database programming employs structural processing advantages that result in accurate information management.
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Aerospace companies have to visualize Big Data so that they can graphically illustrate layers of high-volume information about energy status, distribution and its supply through different channels.
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We all know how the Internet of Things has made it possible to turn everyday devices into sources of raw data for analysis in order to generate business insight.
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Firms use data science aggressively to be a market leader. Data is streaming in from different sources like web, social media, customer reviews, internal databases, and governmental datasets.
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What this simply means is that artificial intelligence can help to improve human life and reduce stress. Here are the benefits of artificial intelligence.
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Machine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends.
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If you're an experienced programmer interested in crunching data, this book will get you started with machine learning a toolkit of algorithms that enables computers to train themselves to automate useful tasks.
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Our fondness for the internet, smartphones, and tablets has created a rich vein of data. Our every action creates heaps of data that can be consumed for data analysis.
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Gain new insights into your data. Learn to apply data science methods and techniques, and acquire analytical skills.
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Big Data has become a new buzz word in the IT industry. This article aims to explain what Big Data really is and how it will be useful in solving problems.
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