Theory of Intelligence
DEEP LEARNING•Neural Networks•Building Networks In Pytorch•4.3 The Training Loop

Introduction

The five lines at the heart of every PyTorch training run, the difference between training and evaluation mode, and how to track metrics and validation loss.

Introduction

In scikit-learn you call model.fit(X, y) and training happens inside. In PyTorch you write the training loop yourself. It sounds like more work, but it's only a few lines — and it gives you complete control and a clear view of what training actually does.

Think of it as a coach running practice sessions: show the player some examples, see how they do, explain the mistakes, let them adjust — and repeat, session after session, checking regularly on a separate test of skills.

Discuss theoretical concepts, mathematical formulas, and architectural foundations.

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