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Once we have the data we need—thousands of sample games—how do we turn it into something the ML can train itself on? That means understanding how training works, and what a model is.
A writer and a software engineer from Google's People + AI Research team explore the human choices that shape machine learning systems by building competing tic-tac-toe agents.