Help me with ideas for "pet project" in ML. • /r/MachineLearning

Well, point 1 and point 2 are hard to simultaneously satisfy, since doing reinforcement learning at scale is pretty much a research topic on its own. Reasoning: the number of decisions it has to make during a game is small, so reinforcement learning should work pretty well. There's a couple of levels of refinement you could try to extend the project - basic model is'given game state, how do I bid?'; first extension is'given game sequence, how do I bid?'; second extension is'given a sequence of previous games with these particular players, how do I bid?'.