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Track 01 · Learning track

Foundations of ML

How machines learn from examples: features, loss, gradient descent, and the eternal fight against overfitting.

For: You know what AI is and want to understand how learning actually works.

8 stops · 8 live · 8 interactive

  1. How the world gets turned into columns.

  2. Why you never grade a model on questions it has seen.

  3. The single number a model tries to shrink.

  4. Rolling downhill toward a better model.

  5. Memorizing the textbook vs understanding the subject.

  6. Predicting numbers, predicting categories.

  7. Finding structure nobody labelled.

  8. Accuracy lies. Here's what to measure instead.

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