Both the intro and this one are great reference books but I don'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.
The text was full of non-trivial errors that genuinely hindered students' understanding. Moreover, the presentation was not particularly enlightening -- lengthy mathematical discussions therein were not neither rigorous enough for a proper mathematical introduction; nor distilled enough for an application practitioners. I understand that Murphy explicitly tried to strike a balance -- I wonder if this balance ended up being in the awkward no man's land.
I do agree that I found the book better as a secondary reference due to its breadth of topics. The second book seems to continue this trend of covering even more topics.
Kudos to the author for putting out a free version and for the work but the number of errors seems crazy high (I checked a couple and doesn't seem like they were fixed in the 2023-06-21 draft pdf he has put on his website), I have the 2022 book so definitely have to look into the error list.
https://github.com/probml/pml-book/issues?page=12&q=is%3Aiss...
But for those with no ML background, the place to start is: https://mml-book.github.io/
[1] https://www.microsoft.com/en-us/research/uploads/prod/2006/0...