Answers.Body: <p>I don't know much about the Haykin's book.</p>
  <p>The Bishop book seem to be the standard text for a graduate-level course in CS departments in top research universities.</p>
  <p>I remember back in the day when I took the ML course, the professor used the Bishop book and was very fond of it.</p>
  <p>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.</p>
  <p>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.</p>
  
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Answers.CreationDate: 2022-08-14T03:18:45.647Z
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Body: <p>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.</p>
  <p>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.</p>
  <p>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!</p>
  <p>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 &quot;induced local field&quot;, 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).</p>
  <p>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.</p>
  <p>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.</p>
  <p>Thank you in advance.</p>
  
Tags: <neural-networks><machine-learning><books>
Title: Machine Learning book for fundamentals - Simon Haykin vs. Christopher M. Bishop
UserDisplayName: Rubem Pacelli
ThreadText: # Machine Learning book for fundamentals - Simon Haykin vs. Christopher M. Bishop
  
  (Asked by: username_0 on 2022-08-13)
  
  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.
  
  **Tags:** neural-networks, machine-learning, books
  
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  ## 1 answers
  
  ### Answer by username_1 on 2022-08-14. Score: 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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