Machine Learning

What Hacker News says

1. PheonixPhartsJan 2024
   Reinforcement learning is an entirely separate area of research from LLMs and, while often seen as part of ML (Tom Mitchell's classic Machine Learning has a great section on Q learning, even if it feels a bit dated in other areas) it has little to do with contemporary ML work. Even with things like AlphaGo, what you find is basically work in using deep neural networks as an input into classic RL techniques.

   Sutton and Barto's Reinforcement Learning: An Introduction is widely considered a the definitive intro to the topic.

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2. pixel_tracingDec 2022
   This may not be a sexy idea but one example I can thing of Tom Mitchell’s Machine Learning book, it gives the bare bones of what machine learning is (albeit it is missing some of the newer architectures) but that gives a great overview of how to build these architectures from scratch
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3. pietroppeterJul 2020
   Tom Mitchell book is still a great book to understand what Machine Learning is about
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4. rrampageApr 2020
   Sure.

   1. Introduction to the Theory of Computation - Sipser and Introduction to Algorithms - CLRS (for the Algorithms course)

   2. Machine Learning - Tom Mitchell

   3. Artificial Intelligence - A Modern Approach - Russell and Norvig

   4. Design of Everyday Things - Norman (for HCI)

   5. Operating Systems in Three Easy Pieces [0]

   Most of the courses had their own notes, slides and suggested research papers as primary reading and the textbooks were mostly used as a secondary reference.

   [0] - http://pages.cs.wisc.edu/~remzi/OSTEP/

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5. neel8986Jan 2018
   This is kind of a masters degree course i created for myself to get knowledge of Machine Learning from bottoms up

   First, you need a strong mathematical base. Otherwise, you can copy paste an algorithm or use an API but you will not get any idea of what is happening inside Following concepts are very essential

   1) Linear Algebra (MIT https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra... ) 2) Probability (Harvard https://www.youtube.com/watch?v=KbB0FjPg0mw )

   Get some basic grasp of machine learning. Get a good intuition of basic concepts

   1) Andrew Ng coursera course (https://www.coursera.org/learn/machine-learning)

   2) Tom Mitchell book (https://www.amazon.com/Machine-Learning-Tom-M-Mitchell/dp/00...)

   Both the above course and book are super easy to follow. You will get a good idea of basic concepts but they lack in depth. Now you should move to more intense books and courses

   You can get more in-depth knowledge of Machine learning from following sources

   1)Nando machine learning course ( https://www.youtube.com/watch?v=w2OtwL5T1ow)

   2)Bishops book (https://www.amazon.in/Pattern-Recognition-Learning-Informati...)

   Especially Bishops book is really deep and covers almost all basic concepts.

   Now for recent advances in Deep learning. I will suggest two brilliant courses from Stanford

   1) Vision ( https://www.youtube.com/watch?v=NfnWJUyUJYU )

   2) NLP ( https://www.youtube.com/watch?v=OQQ-W_63UgQ)

   The Vision course by Karparthy can be a very good introduction to Deep learning. Also, the mother book for deep learning ( http://www.deeplearningbook.org/ )is good

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6. eivarvAug 2015
   Sidenote: I highly recommend Tom Mitchell's (the professor) book as a general introduction to the topic.

   [0]: http://www.amazon.com/Machine-Learning-Tom-M-Mitchell/dp/007...

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