Memory is one of the biggest challenges in deep neural networks (DNNs) today. Researchers are struggling with the limited memory bandwidth of the DRAM devices that have to be used by today's systems to store the huge amounts of weights and activations in DNNs.
Source: Ghraphcore
27882
Technology always takes a dominant position in economy and society. Millions of people therefore found their careers, and many others have even dived into a completely different field just for entering this industry.
Source: HOB25965
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: HOB19743
Python and R are the two most popular programming languages used extensively by Data analysts and Data Scientists. Both the languages are free and open-source and were developed in the 1900s. However, following are some of the reasons which gives Python edge over R that makes it even more popular among the community.
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I have compiled this list of 154 online programming language and Computer Science courses such free online courses that you can start this month.
Source: HOB35157
In Part-2 we have covered first 100 courses in number at an intermediate level. As i have classified these courses on the basis of difficulty level. You can find complete lists of the technology-related courses starting later in 2018 on Class Centrals Computer Science, Data Science, and Programming subject pages.I've sorted these courses into the following categories based on their difficulty level.
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In Part-3 we have covered 50 plus courses at an intermediate level. As i have classified these courses on the basis of difficulty level.Many of these courses are completely self-paced. The rest will start at various times later in September. You can find complete lists of the technology-related courses starting later in 2018 on Class Centrals Computer Science, Data Science, and Programming subject pages.
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In Part-3 we have covered 50 plus courses at an intermediate level. As I have classified these courses on the basis of their difficulty level.Many of these courses are completely self-paced.
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In Part-4 we have covered first 100 courses in number at an intermediate level. As i have classified these courses on the basis of difficulty level. You can find complete lists of the technology-related courses starting later in 2018 on Class Centrals Computer Science, Data Science, and Programming subject pages.I've sorted these courses into the following categories based on their difficulty level.
Source: HOB14271
In Part-4 we have covered first 100 courses in number at an intermediate level. As i have classified these courses on the basis of difficulty level. You can find complete lists of the technology-related courses starting later in 2018 on Class Centrals Computer Science, Data Science, and Programming subject pages.I've sorted these courses into the following categories based on their difficulty level.
Source: HOB10797
In Part-5 we have covered first 100 courses in number at an intermediate level. As i have classified these courses on the basis of difficulty level. Here we have mentioned the courses for advanced level.
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In Part-5 we have covered first 100 courses in number at an intermediate level. As i have classified these courses on the basis of difficulty level. Here we have mentioned the courses for advanced level.
Source: HOB15669
In the ever-changing ecosystem of data science tools, you often find yourself needing to learn a new language in order to keep up with.
Source: HOB9468
Coding is a prized skill in today's business environment and software developers proficient in multiple programming languages are highly valued by organizations for their ability to help businesses go digital and carry out vital business functions.
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Over the past 6 months, I've been working on a programming language called Pinecone. I wouldn't call it mature yet, but it already has enough features working to be usable.
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According to the Tiobe Index for September 2018, Java, C, and Python are the most popular programming languages in the world.
Source: HOB144648
Data is not for only Analytics team now as Data Scientists are in demand and data covers all most many roles in an organization and employees need the literacy to handle it effectively. Now in most of the organization the data skills matters a lot because data is gold for all the industries and it is in very huge numbers as well.
Source: HOB8694
The Python language's two main advantages are its "Simplicity" and "Flexibility". Its straightforward syntax and use of indented spaces make it easy to learn, read and share. Soon Python will be the world's most popular coding or programming language among all the languages. In the past 12 months Americans have searched for Python on Google more often than for Kim Kardashian, a reality-TV star.
Source: HOB16227
Considering the extensive number of the modern programming languages, deciding which one to take by its horns and master can be a strenuous task.
Source: HOB34122
Big Data visualisation is among the utmost important components of working with various Big Data analytics solutions. Once the flow of raw data is represented with images, decision making becomes much easier. In order to meet and exceed the customer's expectations, the tools for Big Data visualization should provide a certain set of features.
Source: HOB11241
Python is one of the popular high-level programming languages used in an extensive variety of application domains. The language was created by a Dutch programmer known as Guido van Rossum and initially released in 1991.
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Big Data industry and data science evolve rapidly and progressed a big deal lately, with multiple Big Data projects and tools launched in 2017. This is one of the hottest IT trends of 2018, along with IoT, blockchain, Artificial and Machine Learning.
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Guido van Rossum, a Dutch computer scientist, set himself a Christmas project. Irked by shortcomings in other programming languages, he wanted to build his own. His principles were simple. First, it should be easy to read. Rather than sprawling over line-endings and being broken up by a tangle of curly braces, each chunk would be surrounded with indented white space. Second, it should let users create their own packages of special-purpose coding modules, which could then be made available to others to form the basis of new programs. Third, he wanted a short, unique and slightly mysterious name. He therefore called it after Monty Python, a British comedy group.
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DevOps involves infrastructure provisioning, configuration management, continuous integration and deployment, testing and monitoring. DevOps teams have been closely working with the development teams to manage the lifecycle of applications effectively.
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One of the most important things is to decide what are the best blockchain programming languages and which would be the most beneficial of them for blockchain development.
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Data is absolutely priceless and the new gold for all businesses. But it is not a cake walk to analyze it as greater things come at a greater cost. With the tremendous growth in data, we need a process to extract useful insights from the raw data.
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If you have doubt in your mind regarding the future of data science then definitely you are concerned the techniques and tools such as Python, Hadoop or SAS will become outdated or going ahead in a data science course will be beneficial for your career in the long-run or not.
Source: HOB7467
Your business may need a dynamic web-based solution, however; the extensive range of options available in the case of programming languages may leave you confused. It is important to understand that selecting a language or a platform in a startup is definitely one of the most crucial decisions. Though there are multiple developmental languages, Python is becoming the most preferred one, especially among startups on account of multiple reasons.
Source: HOB10428
It can't be denied that Big Data is a hot topic in present times. But there are businesses still struggling to shift from concept to execution. The only new thing which allows us to make sense of this information is analytics. The primary goal of analytics is the exploration or application of analytic techniques to large amounts of information in variety of types including unstructured data which comprises of text strings, sound and movie files, documents, images, geo-location data, and documents.
Source: HOB7122
The field of data is concerned with mining the huge volume of data flowing into the organization's warehouses via effective and proper application of scientific and mathematical skills at the same time.
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Data science is basically the application of a combination of mathematical, statistical, analytical and programming skills for the collection, organization, and interpretation of data to allow effective and proper management of the business whose data it is.
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Python is commonly compared to different understood languages like Java, JavaScript, Perl, Tcl, or Smalltalk. Comparisons to C++, Common Lisp and theme can even be enlightening. During this section, I'll shortly compare Python with all those languages.
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To make the system more effective it is necessary to choose the right platform for an IT project. All languages are not the same, either its German, French or Japanese we always choose languages which will suit us, but how do we get to know that which is the best and what will suit us. According to the software that you have planned, there are possibilities that many programming solutions might have misfits. All you need is to choose the best language that fits your software by recognizing that your software does not perform in a sequence which is unpredictable, software is complex or not, what are the hardware and operating platform on which the software should be able to run on.
Source: HOB7986
Python, the in-demand programming language. This is what everyone is saying. In fact, it is the most recommended programming languages for beginners. Students who are starting their career are advised to start with the programming language called Python. But, why is it so? Why only Python and not other programming languages? What does Python have that makes it so easy?
Source: HOB10425
The majority of artificial intelligence (AI) research to date has been focused on the vision. Thanks to machine learning, and in particular deep learning, we now have robots and devices that have a pretty good visual understanding of their environment.
Source: HOB11649
Nothing is quite so personal for programmers as what language they use. Why a data scientist, engineer, or application developer picks one over the other has as much to do with personal preference and their employers' IT culture as it does the qualities and characteristics of the language itself. But when it comes to big data, there are some definite patterns that emerge.
Source: HOB31926
There's most hype concerning frontend technologies like Vue.js, AngularJS, ReactJS within the web development domain, it gets straightforward to ignore the backend. Normally, users are additional doubtless to note what is served before their eyes and not observe of what goes behind the scenes. Backend web development involves the part of coding that isn't seen by the user. Most often, backend web developers are liable for the code behind juggling data to and from the frontend.
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Skills of data analytics have become the leading factor in terms of the advanced development and for the career perspective, the demand of the data analyst is increasing day by day. There are several online courses which you would prefer if you want to build your career as a data analyst as it will help you to learn the fundamentals of data science, the key tools of data science and the study of programming languages in the analysis of big data.
Source: HOB14202
The selection process of data scientists at Google gives higher priority to candidates with strong background in statistics and mathematics. Not just Google, other top companies (Amazon, Airbnb, Uber etc) in the world also prefer candidates with strong fundamentals rather than mere know-how in data science.
Source: HOB10905
The rates of unemployment are at a lower phase and the economy is booming. There are many companies who are facing the shortage of data engineers and wanted some professionals with high skills. It is really difficult to get skills for both data scientist and data engineer in the same file while taking the step towards it is the personal choice which profiles you want your career to be in.
Source: HOB11889
In the ever-changing ecosystem of data science tools, you often find yourself needing to learn a new language in order to keep up with the newest methods or to more effectively collaborate with coworkers.
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Data Analytics tools, latest technologies, and programming languages are required by data science which helps the data scientists to gain meaningful insights and value from the data. A recent survey of nearly 24,000 data professionals by Kaggle revealed that Python, SQL, and R are the most popular programming languages. The most popular programming language was Python 83% used. 3 out of 4 data professionals recommended Data Scientist should learn Python programming language.
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As requested, I'm publishing this guide for those wishing to choose between Python and R Programming languages for Data Science. You may be new to Data Science or you need to pick one choice on a project, this guide will help you.
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This video will show you the top four programming languages to learn in 2019 to get a job without a college degree. The way that I've ranked these languages they are based on three things number firstly, the time it takes even an absolute beginner to go from complete zero and ultimately getting a job without needing a college degree, Job Market: now this is the most important one you guys this is what you're here for the salary and how much money are you making? Productivity: how fast can you go from conception of an idea to a completely coated application that another person can use.
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Artificial intelligence and Machine learning have penetrated every sector. So, if you want to get to college, maybe an artificial intelligence robot will determine if you can get in. You see a car playing on the road which is driverless, after noticing it you know that there is the role of artificial intelligence in it. How can the software development be left behind?
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As a computer science student, you don't need to totally rely on the knowledge that you just get from the room. You must focus on the far side that. On condition that computing may be a terribly wide field, the information from the room is definitely not enough. You must try to browse the most effective computing books.
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There is huge material for the people who are interested in the machine learning with python. As we moved to the new year 2019, it is a good time to again visit the concept and get the way for the new learning path for mastering machine learning with Python.
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Cloud engineers professionals responsible for assessing a business's infrastructure and migrating different functions to a cloud-based system are in high demand, as more companies move critical business processes and applications to public, private, and hybrid cloud infrastructures.
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How to learn to code? Best resources available online? How to choose a personal project to work on? Thoughts on getting a computer science degree or going to coding boot camp!
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One of the hardest questions will face is when you start tackling programming, is what language should I learn first. Let us talk through some of the concerns that you might have, it feels like if you choose a language that you are making a final decision about what you're going to be doing for the rest of your life.
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This is going to be an ambitious video as here ten languages are discussed just to give you an overview because people are always asking. What do you think of this? What do you think it would even use C++? What do you think of C? What do you think of prepped Python? Where do you think of Ruby? What do you think of sleuth?
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Developers are the main tech professionals in the organization with increased demand and talent shortages leading to large salaries for many of those in the field. Software development is a dynamic field, in which new programming languages, frameworks, and technologies are included and this job needs constantly change.
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People waiting to learn python have the option as Mike Dane created this in-depth video course for Python. There are several programming languages but Python is the priority of every individual.
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There are several programming languages like Java, C++, Python, and so forth. Due to higher demand, it is really easy to learn common languages, but there is a drawback in it, as there are many who are learning that language which brings up a higher level of competition and it becomes tough to command the highest pay rates.
Source: HOB20991
Online classes help you to build your resume, and there are several cases in which many people have made a transition from a marketing role to a tech role and made them much more marketable in a job market where tech rules.
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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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Here are some courses in Data Science which will take you to the real world of data science.
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Machine Learning has a growing career with nearly every of the IT, Financial, Healthcare using Machine Learning to solve bigger issues and challenges.
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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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The Graphics supported by R and its statistical features are considered better than SAS.
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We always hear from some or the other person about a developer, hacker, or a computer scientist.
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The role of a Data Scientist depends most on the organization he is working on.
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It can't be denied that Big Data is a hot topic in present times. But there are businesses still struggling to shift from concept to execution.
Source: HOB9312
C and C++ is a language which is not often used in your profession but it will give you a lesson for a lifetime.
Source: HOB31230
In many of the cases, aspirants do not know about the responsibilities each position carries. I have discussed two such roles here, Statisticians and Data Engineer which are confused a lot by the aspirants.
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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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So it is a mix of programmatic and business concerns about each of the programming languages.
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Which Programming Language most of the hackers use? So, here we can see that hackers use multiple languages.
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This article discusses those top 3 skills which are required by every Data scientist and it won't be wrong to say that these 3 skills are like the 3 keys in unlocking your success-door in the field. It thus becomes very important that you take these 3 skills very sincerely and start developing them right from today.
Source: HOB6681
Are you thinking that from where would you learn Python Programming Language? So here are multiple resources to go through.
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Look. Facts and facts. They are not made by anyone. It is just what is happening. Here are some numbers. By all the numbers here are US market only.
Source: HOB5343
Python Programming language should be on the tips for beginners and professionals.
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The future of Machine Learning is bright and if you have really thought over of getting your career started in Machine Learning than I must say -" You have made the right choice for your future". Here I have arrived with some of the most important points you need to successfully start your career.
Source: HOB11499
Based on my brief tryst with programming, I strongly recommend the following websites for learning C, C++, and Java.
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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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Here are some books for learning some famous programming languages like Java, C++, C and many more.
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If we see, the demand for programming languages skills like Java and PHP is increasing day by day and the salary offered is also rising rapidly.
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Chatbots are of immense importance in the present times where using chatbots majority of the tasks in the companies like promotional campaigns, branding, customer services and queries are easily handled using chatbots.
Source: HOB8049
IPL (Information Processing Language) was the first language developed for artificial intelligence. The language included features to perform general problem solutions.
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With regard to a Data Scientist apart from the soft skills and the business acumen technical skills also becomes a very important part.
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A Big Data Analyst is the person in the organization who collects data from various resources, clean it for further processing, converts it into another format which is easy to analyze (also called Data Munging) and finally analyze it for finding hidden patterns and useful information from it (also called insights).
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About $100,000 a year. That's the answer if you have been programming for 4+ years and work in a major tech hub like the Bay area or NYC.
Source: HOB7428
Let's keep up everything in brief: If a C++ class definition takes up more than 1,000 lines, it's a pretty good indication that the class has multiple responsibilities and needs to be broken up.
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In this tutorial, you will learn the concept of computer programming and the types of programming languages available,
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Some of the job roles in IT are so interlinked that it becomes difficult to segregate them often. The role of a Programmer and a Software Developer fall in that category. In this article we will try to clear this big confusion and will take you in depth of the responsibilities handled by both and the differences the two of the roles carry.
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Here are some videos of machine learning frameworks which are divided into 3 parts.
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Here are few ways to improve from a Junior or Mid-level Python developer to a total coding rockstar.
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Machine learning has been one of the top tech new topics in recent months and is now being widely applied to businesses. Briefly, machine learning (ML) is an application of AI (artificial intelligence) that allows systems to learn and improve without being directly programmed.
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Without a College Degree. How we're gonna rank these programming languages from number five to number one is based on three things.
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Becoming a good programmer is incredibly difficult and it doesn't happen quickly. We can't expect to plant some trees and have 2000-year-old redwoods grow overnight, regardless of the demand for them.
Source: HOB242583
Machine learning and artificial intelligence are growing fields and growing topics of study. While the advanced implementations of machine learning we hear about in the news might sound scary and inaccessible, the core concepts are actually pretty easy to grasp. Here is the list of the most popular resources for machine learning beginners. Some of these books will require familiarity with some coding languages and math, but we'll be sure to mention it when that's the case.
Source: HOB8241
What is a programming language? I'd say it was a computer language you could use to make a computer do a series of actions. This is why HTML, for example, ISN'T a programming language, since it just specifies how text and images should be displayed on a website.
Source: HOB6333
As you can see that PubG is the most top-rated game across all the platforms having 2 million daily users all over the world.
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Lots of students have been a success with getting their first job or promotion after going through these courses.
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In this article, you will get to know some of the best frameworks to get you started with AI development.
Source: HOB7749
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.
Source: HOB7242
Learning to code is not only necessary if you're looking to start a lucrative career as a computer programmer, but it's also an incredibly useful skill that will help you develop in-demand job skills.
Source: HOB14805
Here are some resources to learn deep learning frameworks.
Source: HOB7536
Both Java and JavaScript have commonly used web technologies. The similarities between their names often make beginners feel that JavaScript and Java are related.
Source: HOB6405
The Cyber Threat is real and may have grave long-term consequences for those at the receiving end of a cyber attack.
Source: HOB5652
If you are an amateur who's inclined on knowing the Java programming language inside out, doing this will undoubtedly pave your way for timely execution of simple and complex Java development projects.
Source: HOB6273
First of all, it is important to understand that Machine Learning is basically a subset of Artificial Intelligence. ML is the process using which AI learns.
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One of the buzz words in computer gaming today is 'artificial intelligence'. All right, so that's two words really, but let's not be too picky.
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Data Science refers to studying hidden insights behind the data and manipulating them in order to find logical solutions to problems in business and industrial contexts.
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These books provide multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.
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The confusion often arises from the fact that there is an overlap with regard to programming skills. Listed below are some of the key differences between Software development and Data Analytics:
Source: HOB5337
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