One of the best books for beginners in data science. Especially the machine learning is lucid and very practical for practice. I used Octave to test the programs, worked well for me. Highly recommend. ( )

Updated Disclaimer: I received this book as a Member Giveaway. No compensation was received other than the chance to read this work. This is an edited review in response to an updated version of the work I received.

Note: This review has been completely rewritten as the entire finished work has now been made available to me, and in the interest of clarity and honesty, my previous review rating was 3 and a half stars for the previously unfinished work.

Summary: This work is an attempt to help readers learn how to gain proficiency in using the R programming language for data science and data analysis within a short period.

The book itself is a fairly technical manual on how to use R for data analysis. There are coding examples throughout, such as one used to show how the R language would look if a user was trying to create a specific type of graph. The book takes you through data wrangling, the maths involved, prediction modeling, data classifications, and various other R program features.

The graphs illustrated further on in the book are both visually appealing and informative. The chapter discussing the various maths was an excellent summation of what a user would need to know for using R for data analysis and the graphing elements involved.

A nice addition from the previously reviewed copy I had received was the introduction of two "Hands on Projects" which gave the reader links to data sets to work with and walked the reader through how to use those data sets by first loading them into the R program, then viewing the data structure, and ending with showing how to show the data outcomes visually through charts and graphs, with various outcomes listed and illustrated. Another nice addition was the chapter on use cases for using the R programming language.

Overall, this final version was a vastly improved and much more impressive work than the previous two versions I had read, and I am pleased at the results of their work.

I would recommend this book for those who may be curious about R programming, those in the data science field that are looking for new ways to confront data, and those programmers who like to take on a challenge. ( )

Generally, it takes several months to achieve proficiency in Data science. This book is an attempt to achieve proficiency in one month.

website - dswithr.ml ( )