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≫ Descargar Gratis R Programming for Data Science Roger Peng 9781365056826 Books

R Programming for Data Science Roger Peng 9781365056826 Books



Download As PDF : R Programming for Data Science Roger Peng 9781365056826 Books

Download PDF R Programming for Data Science Roger Peng 9781365056826 Books

Data science has taken the world by storm. Every field of study and area of business has been affected as people increasingly realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it an invaluable tool for data scientists around the world. This book is about the fundamentals of R programming. You will get started with the basics of the language, learn how to manipulate datasets, how to write functions, and how to debug and optimize code. With the fundamentals provided in this book, you will have a solid foundation on which to build your data science toolbox.

R Programming for Data Science Roger Peng 9781365056826 Books

I bought this book as a companion to the Data Science course on Coursera and immediately sent it back.

I had hoped that this would serve as good reference material for the course. Instead it was full of you tube links to videos working through examples.

I wasn't amused when I discovered that I had paid for a printed list of you tube links.

Product details

  • Paperback 194 pages
  • Publisher lulu.com (April 20, 2016)
  • Language English
  • ISBN-10 1365056821

Read R Programming for Data Science Roger Peng 9781365056826 Books

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R Programming for Data Science Roger Peng 9781365056826 Books Reviews


Excellent content for beginners. It has been used in parallel of R programming classes in Coursera.org.
This book was the accompaniment for the Data Science with R course in Coursera. It was a good supplement to the course lectures, and I have a feeling it will be handy as a reference book as I go forward in learning data science.
This is the book to get when you want to raise your R skills from knowing how to use existing functions to knowing how R works under the hood. It covers introductory topics like what is a vector, list, etc but it also gives a good first presentation on topics that are left out of introductory books. You will pick up the vocabulary you need to read advanced books. Easy to understand topics, like what are formal arguments, free variables, lazy evaluation etc. are presented without distractions. The coverage on confusing topics like single and double square-bracket notation is some of the best out there. Advanced topics like scoping rules and functions that return functions are also well covered.

This book is also a nice bridge between old school R programming styles and the modern Tidyverse mindset. You will get an excellent first look at many of the libraries that are in the Tidyverse.

The book does contain links to videos covering the same material. The visuals and the content is very solid but the videos are hard to listen to because the author has not worked with a speech coach to learn to stop saying umm.

If you are living on a tight budget ... the author allows you to buy this book on a sliding scale at learnpub.

Overall, this book is superb and is a must for anyone who wants to be "good" at R.
Best book ever to get you started on R.
This material is helpful but this book has so many typos that it becomes a distraction.
I bought this book as a companion to the Data Science course on Coursera and immediately sent it back.

I had hoped that this would serve as good reference material for the course. Instead it was full of you tube links to videos working through examples.

I wasn't amused when I discovered that I had paid for a printed list of you tube links.
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