The book in the original post and the other book from the same author are short surface-level summaries of the field that don't go in depth at all and don't provide any meaningful new content. It's like someone took their personal notes, formatted them in a pdf and called them a book. It's an embarrasingly transparent cash grab or just something that helps the author's social media presence because they can now say that they "have written an ML book".
>the other book from the same author are short surface-level summaries of the field that don't go in depth at all
Isn't this the entire point of the 100 page Machine Learning Book? An introduction for new practitioners?
> It's like someone took their personal notes, formatted them in a pdf and called them a book.
Why is that such a bad thing? I like condensed, reader's digests versions of things. Not every text has to break new ground; some of it can be, well, purely educational.
Or do you dispute the educational value of the text?
Legitimately curious; I haven't read any of the books, but I actually like the way you described the author's text process.
I agree - "new material" is actually a concern in the context of a text book. I feel that synthesizing and presenting a coherent view of the communities best practice is a very valuable thing.
I think (but am very open to correction) that this is now a very hard thing for academics to do - the incentive for writing a text book is very low because they are not esteemed or counted as research? Writing a book like this is very hard.
I am pretty interested actually as I am currently trying to write a similar book of my own! I can see a lot of difference between this and what I am trying to do, and may differences to "Hands on" but what in particular are you disappointed with here?