Welcome to another roundup of new additions to the Big Book of R collection of almost 400 books!

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Thank you to Michael Harris and Jim for their submissions!

Neural Cryptography Using Keras in R

by Michael Harris

This book illustrates a method of using the traditional deep learning-based multi-class classification techniques to hide messages in a matrix of seemingly random numbers. This book is definitely a niche topic and is more of a fun project than something you would want to do for work. The premise is that you can represent characters as a sequence of random numbers you uniquely generate, and with the help of a neural network, a message can be embedded in a matrix of numbers. In the book, I also describe how this method can be used to embed messages in images.

https://www.bigbookofr.com/machine-learning#neural-cryptography-using-keras-in-r

Neural Networks with Keras in R: A QuickStart Guide

by Michael Harris

I wrote this book for people who primarily use other statistical software like SPSS or SAS, and want to get started in deep learning with Keras. With this idea in mind, a sizable chuck of the book is giving people the prerequisite information they need to start using Keras. I start from the very beginning of assigning variables and end with multi-class classification with deep learning models.

https://www.bigbookofr.com/machine-learning#neural-networks-with-keras-in-r-a-quickstart-guide

Learn Version Control with Git

by Tower

Get started with Git with this beginner-friendly course. This free online book will help you learn and master version control it with ease.

https://www.bigbookofr.com/version-control#learn-version-control-with-git

Linear Algebra for Data Science with examples in R

by Shaina Race Bennett

This course is meant to instill a working knowledge of linear algebra terminology and to lay the foundations of advanced data mining techniques like Principal Component Analysis, Factor Analysis, Collaborative Filtering, Correspondence Analysis, Network Analysis, Support Vector Machines and many more.

https://www.bigbookofr.com/field-specific#linear-algebra-for-data-science-with-examples-in-r

Spatial Statistics for Data Science: Theory and Practice with R

by Paula Moraga

The book combines theory and practice using real-world data science examples such as disease risk mapping, air pollution prediction, species distribution modeling, crime mapping, and real state analyses.

https://www.bigbookofr.com/geospatial#spatial-statistics-for-data-science-theory-and-practice-with-r

Art from Code

by Danielle Navarro

This workshop provides a hands-on introduction to generative art in R. You’ll learn artistic techniques that generative artists use regularly in their work including flow fields, iterative function systems, and more. You’ll also learn about R packages specialised for generative art.

https://www.bigbookofr.com/art#art-from-code

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The post 6 New books added to Big Book of R appeared first on Oscar Baruffa.