Answers.Body: <p>This right here is the money shot.</p>
  <p><a href="https://ocw.mit.edu/courses/18-05-introduction-to-probability-and-statistics-spring-2022/pages/classes-reading-and-in-class-materials/" rel="nofollow noreferrer">https://ocw.mit.edu/courses/18-05-introduction-to-probability-and-statistics-spring-2022/pages/classes-reading-and-in-class-materials/</a></p>
  <p>That's essentially what you're looking for. They get into Bayesian Inferences at Unit 2. This is better than a textbook, it has courses, lectures, problem sets, and if you're ever confused just ask a LLM for an  answer; and yes it has a textbook inside of it too.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-04-24T12:19:22.973Z
Answers.Text: This is just an amazing material! As you mentioned, just what I’m looking for ! 
  Thanks for the recommendation, this definitely answers my question. Thanks Joseph
Answers.UserDisplayName: John Pinto
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-04-28T02:15:52.953Z
Answers.Text: of course! Always happy to help :D
Answers.UserDisplayName: Joseph
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-04-23T07:59:44.833Z
Answers.LastActivityDate: 2024-04-23T07:59:44.833Z
Answers.UserDisplayName: Joseph
Body: <p>I am in the process of learning ML and AI. I've been taking some courses, and I now understand the foundations of the big picture of Machine Learning. I've been using <a href="https://www.microsoft.com/en-us/research/people/cmbishop/prml-book/" rel="nofollow noreferrer">Pattern Recognition and Machine Learning</a> as my go-to-book.</p>
  <p>After a few reads of the chapters I've covered so far, I think I understand the general concepts in each of the methodologies, BUT I do recognize that my probability foundations are weak, therefore I want to improve that: <em><strong>Are there any recommendations on (good) books about probability theory that I could benefit from?</strong></em></p>
  <p>*(good) : by <em>good</em> I mean a book that gives you not only the theory and practice exercises, but especially <em><strong>a book that provides you with the Intuition and practical meaning of the topic being taught</strong></em>; I believe that is why I love Bishop's book because he tries to explain what the equations mean, what the concept implies, and what in practice is used. I looking for the same but on probability theory.</p>
  <p>More specifically, I found that I could not completely grasp the Bayesian framework. I would want to go over it in a probability book. I believe it doesn't hurt from the foundations all the way to the full Bayesian framework theory. by the way, if there are any compilations of topics on which I should focus, it would be highly appreciated as well.</p>
  <p>Thanks in advance,</p>
  <p>Cheers</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-04-21T21:01:03.957Z
Comments.Text: well bishop just published a new book, though it's not strictly on prob theory, and depends what you want to learn about probability theory
Comments.UserDisplayName: Alberto
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-04-24T12:17:07.957Z
Comments.Text: Thanks, I did notice his new Deep Learning book. It’s definitely in queue for reading… thanks!
Comments.UserDisplayName: John Pinto
Tags: <machine-learning><books><probability-theory>
Title: Book(s) recomendation for Probability Theory Foundations
UserDisplayName: John Pinto
ThreadText: # Book(s) recomendation for Probability Theory Foundations
  
  (Asked by: username_0 on 2024-04-21)
  
  I am in the process of learning ML and AI. I've been taking some courses, and I now understand the foundations of the big picture of Machine Learning. I've been using [Pattern Recognition and Machine Learning](https://www.microsoft.com/en-us/research/people/cmbishop/prml-book/) as my go-to-book.
  
  After a few reads of the chapters I've covered so far, I think I understand the general concepts in each of the methodologies, BUT I do recognize that my probability foundations are weak, therefore I want to improve that: ***Are there any recommendations on (good) books about probability theory that I could benefit from?***
  
  \*(good) : by *good* I mean a book that gives you not only the theory and practice exercises, but especially ***a book that provides you with the Intuition and practical meaning of the topic being taught***; I believe that is why I love Bishop's book because he tries to explain what the equations mean, what the concept implies, and what in practice is used. I looking for the same but on probability theory.
  
  More specifically, I found that I could not completely grasp the Bayesian framework. I would want to go over it in a probability book. I believe it doesn't hurt from the foundations all the way to the full Bayesian framework theory. by the way, if there are any compilations of topics on which I should focus, it would be highly appreciated as well.
  
  Thanks in advance,
  
  Cheers
  
  **Tags:** machine-learning, books, probability-theory
  > **Comments:**
  > **username_1**: well bishop just published a new book, though it's not strictly on prob theory, and depends what you want to learn about probability theory  
  > **username_0**: Thanks, I did notice his new Deep Learning book. It’s definitely in queue for reading… thanks!  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2024-04-23. Score: 1 | Accepted answer
  
  This right here is the money shot.
  
  <https://ocw.mit.edu/courses/18-05-introduction-to-probability-and-statistics-spring-2022/pages/classes-reading-and-in-class-materials/>
  
  That's essentially what you're looking for. They get into Bayesian Inferences at Unit 2. This is better than a textbook, it has courses, lectures, problem sets, and if you're ever confused just ask a LLM for an answer; and yes it has a textbook inside of it too.
  
  > **Comments:**
  > **username_0**: This is just an amazing material! As you mentioned, just what I’m looking for !  Thanks for the recommendation, this definitely answers my question. Thanks Joseph  
  > **username_2**: of course! Always happy to help :D  
  
  ---
  
  