Must have book if you want to embark on the journey of data analysis or data science. Each chapter covers one specific algorithm or topic. The best part of this book is it has R code at the end of every chapter so you can try out that algorithm in practice. That allows you to quickly apply the algorithm on real life data. This book can make you productive very quickly. This book is for the practitioners who want to know the purpose of each algorithm and then how to use it and when to use etc. On the other hand his other book is great for graduate and Phd students who want to take deep dive in each topic. That book is good for understanding nuts and bolts of the algorithms. Basically proofs etc
It is an asset. Who are interested in data science from any discipline should choose this book as their hand book. Written in simple language, easily implemented and explained the mathematical/statistical concept in real-life and merge with application in R. Very fantastic book.
I am still going through this book but have gone through enough to write a review. The book is really good one to understand the different class of problems and algorithms that we have with data and the predictions you can make with them. The language of the book is very lucid and helps in having a read through quite easily. The other good part is the algorithms and its concepts are discussed in reasonable detail without delving deep into the mathematical proof of the core formula relating to these algorithms which is very good for people who have lost touch with hard core mathematics so to speak. Another very good part is each chapter has an Lab of sorts where it uses R to show examples of how a particular learning model can be put in place with the data sets. All in all it is a self contained book. So just have to install R and you get going into a very interesting journey with data and its learning algorithms. 5 stars from me for this wonderful effort in compiling this book for the authors.
Reding like story book. Intricate concepts eluciadated with ease and with less mathematical complexity. After reading .pdf version i realised i must have hard copy of this. One thing don’t lend this book to your colleges rather ask them to have their own personal copy.