Probabilistic Machine Learning: Advanced Topics

Related:<p><i>Probabilistic Machine Learning: Advanced Topics</i> - <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=30552869">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=30552869</a> - March 2022 (43 comments)

Both the intro and this one are great reference books but I don&#x27;t find them suitable to study as the main textbook. They cover a large number of topics so the depth of each topic is pretty limited. Keep in mind if you are considering to study these.

I find myself wishing for a book that instead of listing techniques with a few shallow examples per technique , would instead focus on a meaty problem and then apply different techniques to it iteratively showing how a practitioner would derive value. Is anyone aware of such books ?

1200 pages? Do you really read this straight through or just refer to it? That is over whelming to me at least.

The introduction book and link to code is at &quot;book1.html&quot;

Judging from the table of contents, he probably could have dropped the &quot;probabilistic&quot; from the title and just called it &quot;machine learning&quot;.