Small machine learning programs and examples built with numpy; sklearn used for benchmark scores only.
these are not built to be computationally efficient (obviously, if you look at them), but to get a better handle on how things work.
Rough analog to sklearn linear regression, using gradient descent.
Rough analog to sklearn logistic regression, using gradient descent.
learns to play the dice game Farkle
Scoring is hard coded; decisions about whether to re-roll or quit with current score are learned by playing a large number of games, altering strategy, and calculating the gradient of score with respect to strategic changes. Interesting because the gradient of decision making algorithm is not well behaved.
