AI

This course teaches you how to honestly judge whether a trained model is actually good, going beyond the misleading simplicity of raw accuracy. You'll learn precision, recall, the confusion matrix, and the regression error metrics that reveal what a model is really getting right and wrong. This is part 4 of the Applied Machine Learning track, building on Supervised Learning in Practice, Unsupervised Learning & Clustering, and Feature Engineering for ML.

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