Why Your Model Lies When You Have Little Data (Bayesian Inference Explained)
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Why Your Model Lies When You Have Little Data (Bayesian Inference Explained)
Maximum Likelihood Estimation (MLE) is powerful, but it has a fatal flaw: It is naive. If you flip a coin 5 times and get 5 Heads, MLE assumes the probability of Heads is 100%. It overfits to small data. So, how do we stop our models from hallucinating patterns when data is scarce? We use Bayesian Inference. In this video, we decode the math ...
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