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A comment on Machine Learning (1997). Parent comment

Re:Machine Learning (1997) by teruakohatu on Monday August 15, 2022 @11:32PM (#32478905)
It looks pretty good. The introduction, ANN and Bayesian chapters look just as relevant today as they would have been when this book was published, 25 years ago. I like that hypotheses testing is covered.

Chapter 9, Genetic Algorithms and Programming, was hot stuff back then, and research continues today, I went to an interesting seminar a few months ago given by a genetic programming researcher, but from the perspective of solving a ML problem, less useful to the beginner. If you have a regression of classification problem, few people will be trying genetic algorithms to solve it.

Chapter 10 - 12 is rule based systems, for example Prolog, which again was thought of being the future back then, and as much as I love using Prolog, it is not part of modern ML curriculum.

Chapter 13 is short chapter on RL, which is popular today (DeepMind).

All that said, if a beginner wants to pick one book, I would suggest ISLR2, also free and has a Edx course

https://www.statlearning.com/

https://www.edx.org/course/statistical-learning

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Re:Machine Learning (1997) by 082349872349872 on Tuesday August 16, 2022 @08:54AM (#32482133)
RL ca. 1961: https://en.wikipedia.org/wiki/Matchbox_Educable_Noughts_and_...

(which I learned about from a Fred Saberhagen short)

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Re:Machine Learning (1997) by harry8 on Tuesday August 16, 2022 @12:53AM (#32479327)
Is that the same one that was on the stanford edx clone site?

edx seems to be putting more behind a paywall and jacking up the price in a way that's pretty disappointing. That one is what $150 for the computer to tell you if the numbers you typed in some boxes is what was expected, for example. I mean, looking up the answer in the back of the book is worth that? The certificate is worth absolutely nothing to anyone save for how it makes them feel.

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