Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series)

The book is very good but the cover is torn. The book is definitely a new book but its book cover is so torn that it looks like an used book.

I've read a lot of books on ML, and AI, but this one is unusual - its clear, understandable and explains complex probability concepts used in probabilistic ML is a very clear manner. The author not only has the knowledge and grounding but the written eloquence to teach/explain/clarify for the reader. A great read and one I intend to keep around in paper and electronic form if I can get it - money well spent.

Very nice book from the content perspective but the paper quality of such a expensive book is not up to the mark.

As a mid-career software professional trying to get into ML, this book is pure Gold. It has helped me get through Stanford ML classes CS 229 228 224N. The printed version is even more engaging. Theory is explained in an intuitive way with a perfect mix of visuals. Curated materials from thousands of recent papers and books are presented in a delightful and approachable manner. Definitely get the printed hardcover copy! You won't put it down until you've transformed your understanding of ML in a big way!Thank you Kevin Patrick Murphy for sharing your wisdom and putting in enormous effort to create yet another masterpiece. Your contributions to the field of ML and in teaching are well appreciated. God Bless!

The content is great, no need to say more, but amazon delivery is subpar, the corners are easily destroyed.

Very well written and down to the basic. The book requires a good mathematical foundation to be able to read it.

I have both the old version and new version of this book. Great read for anyone who wants to understand ML theory especially for grad students or researchers in the field.

I'm impressed by the consistency, depth, and also recency of the topics covered. Recommended for all PhD students who want to learn ML at the research level.

In all honesty, I love this book so much. Currently studying prerequisites for Machine Learning and it comes in really handy, of course there are many concepts I'm entirely new to in the textbook but I believe with time, I'll be comfortable with it.The contents are well arranged, the notations are also explained in case the notations you familiar with is different hence making switching easy.I'll be updating as I utilize this great masterpiece

I am an applied scientist at a major tech company and first version of this book helped me immensely during my MS program. I have read half of this book last week and it is as good as i was expecting it to be.I don't have enough words to praise for both of these volumes and forever be grateful to the author for writing this masterpiece.Note: the book is in colour just like any other MIT press books.

This is a kind of book that every Data Scientist/Applied Science Aspirants and Machine Learning Engineer should read.Everything in the notion of mathematics covered including probabilistic reasoning, visualizations.Print and binding quality of this book is top notch worth the price.Author didn't hide the algorithms and multivariate calculus behind them which is commendable.This is a serious, no nonsense book stands out from everything as a complete package on it's own.

The content is well organized and of high academic quality. Better than online tutorials, I recommend for people interested in master machine learning. I liked the understandable mathematical formulation.On the other hand, I am disappointed with the sheets used in this book. The sheets are thin and almost transparent that distract the reader.

This great book definitely worth a 5-star rating. I minus two stars, since it is badly protected in shipping and I received a damaged copy.