Someone at stack overflow asked for advice about Machine Learning for checkers. Here is my response:
You might want to take a look at the following: Chinook, Upper Confidence Trees, Reinforcement Learning, and Alpha-Beta pruning. I personally like to combine Alpha-Beta Pruning and Upper Confidence Trees (UCT) for perfect information games where each player has less than 10 reasonable moves. You can use Temporal Difference Learning to create a position evaluation function. Game AI is probably the funnest way to learn machine learning.
PS: There is a great story about the former human world champion, Marion Tinsley, and the computer world champion here
https://www.theatlantic.com/technology/archive/2017/07/marion-tinsley-checkers/534111/