Machine Learning Engineering

Like the first one this is an encyclopedia for machine learning. This is not really for beginners or practitioners. All the topics here could be found on the internet. What the book does well if compile a bunch of topic on machine learning together that someone could use for more research. In fact, the authors seems to encourage that throughout. What the book doesn’t do well is explain machine learning. The examples are disconnected. The author jumps in and out of formulas without introducing them or connecting them to text. I think the book would benefit from a chart that pulls it all together.

This book is an exceptional follow through on the part of the author of the 100 page machine learning book. He covers the 'engineering' of machine learning from start to finish. The 100 page machine learning book introduces the reader to machine learning algorithms and the 'math' behind the magic. However, deploying a machine learning solution is much more than the model. The author clearly outlines the principles once must understand to successfully deploy a machine learning solution.

I particularly enjoyed Sections 1.4 and 1.5 when to use and when not to use machine learning. From the discussion one can clearly set forth the criteria establishing when one should pursue a machine learning solution and when one should pursue other alternatives. A brief stop in each section will undoubtedly save many both valuable time and frustration.

Overall, an excellent work. If you are interested in machine learning I highly recommend this book as well as 'The 100 Page Machine Learning Book.'

It is a great source you can use right before interview

No preface, no table of contents, missing page 1 and page 2 .....

This book is mostly redundant from the previous book. Wasn't worth digging through the book to find the new information.

This is a must read for any data scientist looking to transition to a ML engineer role. I have over 3 years of experience in data science at a leading financial services firm and I must say this book has taught me so many new things. This is a treasure of gold written by Andriy. I have read the 100 pages ML book too. Both of his books are a must read and can be a good daily reference.

This is a hands on book and shows how to practically use ML

This book is not one of them, and that's a good thing. Expect to find lots of practical knowledge in this book - I have tons of earmarks!

It is an excellent read for anyone looking to leverage ML to solve business problems at scale. Andriy has done a great job in breaking down tasks needed to move a model to production. It is a perfect follow up to his first book- Hundred Page ML which is a great read as well.

Probably the best textbook on machine learning around. If you just read the "hundred page book" this one is the follow up you can't miss.