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Hi,

I studied the following book. It's codes are written in JavaScript , Python , C++ . The book is a recent and fine introduction on several AI methods.

Here is the book link.

I took a quick look at the content, and it seems there is extremely little machine learning in this book, except for a decision tree in Chapter 2. Mostly genetic algorithms and population-based methods. No neural network. But what they describe may be fun programming experiments.

I think this one is pretty good, albeit for Go not Chess, and it's a bit pricey.
However, it does cover quite a lot specifically for Alpha Zero, and the code code samples do work (with a bit of tweaking last time I tried).

https://www.amazon.com/Deep-Learning-Ga ... 1617295329

This is very good.
"Make Your Own Neural Network" by Tariq Rashid.
A good starting point. It doesn't cover Convolutional NN but all the basics are there.

where my free ebooks at?
There is one free deep learning book i know of
https://github.com/janishar/mit-deep-le ... ngbook.pdf

Rémi Coulom wrote: ↑Mon Oct 07, 2019 2:15 pm I took a quick look at the content, and it seems there is extremely little machine learning in this book, except for a decision tree in Chapter 2. Mostly genetic algorithms and population-based methods. No neural network. But what they describe may be fun programming experiments.

AFAIK genetic algorithms definitly belong to the term "machine learning". Aside from that, genetic algorithms combined with neural networks (mostly NEAT and variations) are an interesting research point, albeit I haven't seen the usage for chess.

asanjuan wrote: ↑Mon Oct 07, 2019 3:24 pm This is very good.
"Make Your Own Neural Network" by Tariq Rashid.
A good starting point. It doesn't cover Convolutional NN but all the basics are there.

I'll second this, for a non academic scatter brain like me, this book explained things really well. I've managed to complete a few home projects since.

Another book that follows up from the above one is A Simple Guide on Machine Learning with Neural Networks - this is short, sweet, and adds bias nodes and things like that.

https://www.amazon.de/Machine-Learning- ... 679&sr=8-6

I find the concept fascinating - whether it's making a machine learn to play space invaders, or an autonomous raspberry pi car, it's amazing to watch the 'learning' process.

You can have a play with a small NN for your own training here - link.

That page suggests that if you want to take things further, have a go with the popular TensorFlow library, which has no been ported into many languages.