well, the wikipedia definition: >Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical a

well, the wikipedia definition: >Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data and thus perform tasks without explicit instructions. So it's about learning via statistics & data. If you don't use data or statistics it's not ML. Chess engines definitely do not fit there. They descend the game tree and evaluate it with an algorithm like minimax. No statistics. No learning. No training (although the static evaluation function might have been trained/tweaked via NNs). I don't know the details of AlphaGo, but I'm guessing it's similar: the concept of the game is hardcoded (game tree,....) while the evaluation of a position is done via NN. the training can be done via games against itself.