Machine Learning with R: Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data

This book is very comprehensive and easy to follow. I would recommend this book to any one learning both R and Machine Learning for the first time as well as a good refresher for practitioners like me.This book comes with 700+ pages detail theory, pictorial explanations and practical examples.

This is the 4th edition of this book. Clearly an already a successful title it's worth noting this version has loads of updated and new content, enough to treat it and evaluate it as an entirely new title.Coming in over 700 pages it’s not a quick or light read. What you will learn is what you know and what you don’t know. Each of the big topics covered, R language constructs, KNN, probabilistic learning, classification, decision trees, forecasting, SVMs are all subjects of large dedicated, detailed titles themselves and yet what you will find here goes far beyond whistle-stop tours or light intros. The book covers many data engineering topics as well as pure ML engineering. This makes it and end-to-end experience and was a solid choice by the author and production team.Technical books live and die by the quality and correctness of code samples and here the code is styled appropriately, the calibre is consistent and the approaches are well chosen. The Diagrams and supporting text breaking down the samples are clear and punchy enough to make the points well without labouring more than is necessary.Overall the writing style is unfussy, the topic breakdowns and key takeaways are well indicated and a genuine learning experience can be had if you invest as well as a very decent lifespan as a reference. I would put this in the top 3 technical titles I have read this year and would expect to dive in to some the chapters again as a guide in my own projects. If you’re interested in R and ML this is an essential title. If you own a previous edition I’d wager the updates and fresh content are worth the money and bookshelf space. Highly recommended.