New Book: Probabilistic Machine Learning
A great machine learning book. Great value for the price. Pretty comprehensive and up-to-date. Good for beginners, but experts will also enjoy it.
By Kevin Murphy, MIT Press (2022).
This is one of the best machine learning books that I purchased in the last few years. Very comprehensive, covering a lot of statistical science too. The level is never too high, despite a few advanced concepts being discussed. There is a lot of focus on applications, especially image processing, and in particular automated character recognition, mostly digits.
The author regularly criticizes non-Bayesian statisticians. However, many of the methods described in the book are non-Bayesian. I was pleasantly surprised to see that my new frequentist concept of dual confidence region (discussed in my new book) is related to credible regions in Bayesian statistics.
Read full book review, here.
Reliability & Quality Management
3 年Bought this book due to the post. Already happy I did. Also got the previous Murphy book, and have just done a quantum leap in understanding. It's great if you like to think through the calculations and see what is under the hood. Thanks!
Data Engineering | Google Certified Cloud Architect and ML Engineer
3 年Thanks for sharing.
Bayesian inference (PhD) | Data Engineer | ML Engineer | Tech lead
3 年Ben Herbst, another one for the office, Prof!