Machine Learning with R - Third Edition: Expert techniques for predictive modeling

This is an outstanding book and by far the best machine learning book of the several I have read. I highly recommend.1) The author writes this in a way that you can perform machine learning tasks in R without any prior experience using R or ML. He gets you up to speed quickly on how to download R Studio and explains everything you need to know about R in order to perform the ML tasks that are described later in the book. He doesn't explain all of the things you can do in R as in many other books, because you don't necessarily need to know everything about R to perform ML tasks and this book is about ML. So this is obviously not a book that is exhaustive of everything possible in R.2) The structure of this book is outstanding and very logical. Within each of the chapters on Machine Learning models, he describes the model and how it works, includes a section covering the model's syntax in R, the strengths and weaknesses of each model, compares the model to the prior models discussed, and then uses that foundation to walk you through an example of applying each model to real data. Within the examples, he uses the 5 steps of a modeling process: 1) collecting data, 2) exploring and prepping the data, 3) training the model, 4) evaluating model performance, and 5) Improving model performance. I love this structure!3) His explanations of everything are outstanding. I've read several ML books and he by far is the best at explaining things in a way that people can clearly understand. If the model involves statistical concepts, he explains what you need to know very well.4) The book covers many ML models: K-Nearest Neighbors, Naive Bayes, Decision Trees, Classification Rules, Regression, Regression Trees, Model Trees, Neural Networks, Support Vector Machines, Association Rules, K-Means Clustering, and Random Forests. For an advanced Data Scientist, this may not seem like an exhaustive list. However, I feel that for a beginning data scientist or someone that is just interested in getting a good overview of data modeling, I feel this is a great choice of model coverage.Bottom line- if you're at all interested in machine learning in R, this is the book to get. If you're already an advanced data scientist with years of experience, this may not be the best text for you, though.

I'd have to say that this book is a simple and clear concise introduction to both R and ML. Probably one of the best books on ML with R I've used. It starts of with a robust introduction to R and stats that'll give you the tools to play around with R. Next, the book goes into the ML with good illustrations using physical representations for easier understanding. It goes on to some vector/component concepts in SVM (obviously) but still retains the intuitive properties of the book. The book chapters, generally, are independent and can be read as stand alone without much loss in understanding. Overall, a great book to give you the confidence to move forward in ML.

Really like how it goes through all of the major models and is easy to read. Learning data science and it's SO HARD to find books that are written for people who are new to the field/not well-versed in all the technical. Loved that this one was so easy to get through!

I received the book just recently. I will update my review of the contents later. Two things I noticed right away are (a) The 'dataspelunking.com' website mentioned above (in the Amazon description) and in the book, is an empty shell; and (b) The link in the preface pointing to a page containing a PDF of color-images of the screenshots/diagrams in the book is broken, leading to a 404 message. The kindest thing one can say about this is that the book has been rushed to publication and released before the associated resources are ready. At worst this is a misrepresentation. While those color figures are not a big loss, this carelessness does not bode well for the attention to detail with which the book was produced, especially since it is in its 3rd edition.Edited: Packt repaired the broken link and contacted me here to point that out. Very nice! I am revising my rating. I will revise again for content after I finish the book!

The book’s explanations of the concepts/algorithms are very clear and easily understandable. Even if you are not into R, I think it is still a great book for simply learning basics of machine learning.

I like this book, as I already took many R courses and boot camps, but practicing doing projects in the book is really a very good experience I went through it.

Easy but i guess this is for programming beginners. I already learned some languages and R programming before so it doesn't help me that much.

Great examples

Ele apresenta elementos essenciais para quem inicia uma jornada em ML. Ele poderia explorar as duas estruturas de trabalho supervisionado e não-supervisionado pqra regressoes com penalização (Ridge, LASSO e Elastic-Net). É possivel encontrar em outros livros da mesma editora.

Llegó en tiempo y en buenas condiciones. Excelente libro de consulta sobre temas selectos de ML. Aunque es sobre R, me enfoco más en la teoría.

If you want to use machine learning to solve problems, or for your job, this book is amazing. It explains the math/statistics involved in the algorithms, and it gives a crash course in R language (though I was already familiar with R before reading this book). This book does an excellent job in explaining how to practically use machine learning to solve real-life problems. I am very happy that I read this book.

Für jemanden, der Machine Learning verstehen will und wenig Erfahrung mit R und Programmierung im allgemeinen hat, ist dies ein absolutes Standardwerk.

It is a good book, only I notice one thing.In the second edition of the e-book of Machine Learing with R the pictures are in colour.In the 3rd edition of the paperback the pictures are not in colour.Keep this in mind.