Gareth James

I was lucky to attend a MOOC course delivered by the authors of this book- Trevor Hastie and Robert Tibshirani, which was offered by Stanford University. The book presents a balanced amount of theory and practice of the Statistical (Machine) Learning topic with not-in-depth emphasis on mathematical details. It provides the right amount of know-how for those interested to start working in the Data Science field and in Machine Learning, in specific.

Unlike many other references the book has an edge, especially for Data Scientists using R, of putting every chapter’s concept into R practice through the end-of-chapter R Labs. It is an excellent practical guide to implement Machine Learning especially that it explains the pros and cons of many algorithms used in addition to the emphasis on data processing and cleaning before doing Learning.

The book is a must-read for any one embarking on the journey of Data Science as a profession.… (meer)