Since I started studying Machine Learning, I was torn between two books in this area, and I could never decide which one is the best to follow.

The first book is widely used and known: Pattern Recognition and Machine Learning, by Christopher Bishop. I've never head about him before, probably because he is a Computer Scientist and I am an Engineer, and he doesn't have many books, AFAIK. But I know that this one I like a bible for machine learning fundamentals.

However, I came across another book: Neural Networks and Learning Machine, by Simon Haykin. I am very familiar with this author since I already read many of his books throughout my graduation on other topics, such as communication systems, signals and systems, adaptive filters, etc... Then I decided to read it and I like it a lot!

However, I realized that Bishop is much more referenced than Simon Haykin regarding machine learning. Furthermore, both books differ a lot with regard to terms. For instance, the term "induced local field", which is largely adopted in the Simon Haykin's book, is not even mentioned once by Bishop (at least, I didn't find it when I looked it up).

All of these aspects make me fell unconformable and doubtful about my book adoption since I could use expressions and terms that I not so used by other authors.

It may be a taste matter, but I do need suggestions whether the Bishop's book is much better than anything else to get the foundations or it is ok to adopt Simon Haykin.

Thank you in advance.


1 Answer 1


I don't know much about the Haykin's book.

The Bishop book seem to be the standard text for a graduate-level course in CS departments in top research universities.

I remember back in the day when I took the ML course, the professor used the Bishop book and was very fond of it.

He said he had read the book three times, once as a undergrad, once as a PhD student, and once when he taught from the book as a professor. And he said after three reads, he finally got every detail in the book.

Basically, he was saying the book was quite dense and written in a way that is not easily penetrable, but once you truly get it, you would appreciate the beauty of exposition style of the book.


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