Peter Harrington holds a Bachelors and a Masters Degrees in Electrical Engineering. He is a professional developer and data scientist. Peter holds five US patents and his work has been published in numerous academic journals.
Unfortunately, in many cases the author doesn't explain what he is trying to achieve with his code snippets.
In short, if you want to "Just do ML", ie, quickly get started and pick up anything else you need along the way, then this book may be for you.
And if you know something about ML, this is a good complement with regard to a practical implementation of ML algorithm.
The author want to write a practical, easy to understand book for ML subject. And I think this book accomplished this object pretty well. Read morePublished 5 months ago by Yeoun Jae Kim
i would rather have two books instead one. one for java, one for machine learning. this book is quite shallow especially if you are a grad student.Published 8 months ago by Yifan Peng
If you want to learn about machine learning, you can't learn about it from this book. Try taking a course, perhaps, but this just doesn't cut it.Published 9 months ago by Dennis Brooks
I first borrowed an electronic copy after losing my hardcopy of Collective Intelligence. I skimmed all of the text and read more thoroughly several sections which appealed to me... Read morePublished 11 months ago by Ryan M. Balfanz
I bought this book to learn more about machine learning and what it is all about. I am a physicist by training, so this is a foreign topic. Read morePublished 14 months ago by Grant Eastland
My main problem with this book is the way the author structure information on the code examples. Again and again he separates data that belongs together into independent data... Read morePublished 19 months ago by Julio Garcia
I'm a software engineer who knows some Python, and needed to dive deep into Machine Learning. Well, I got my hands on Peter's book, and spent the next few weeks learning machine... Read morePublished 19 months ago by KK
I am new to Machine Learning and I found the book a very good hands-on introduction on the subject. The author takes 8 of the Top 10 algorithms in Machine Learning (based on a 2007... Read morePublished 19 months ago by Sujit Pal
This book is a good introduction to the main algorithms used in machine learning: linear/logistics regression, kNN, decision and regression trees, naive Bayes, support vector... Read morePublished 21 months ago by enty