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3.7 Feature Normalization (Parts 1-2)

3.6 Training a Logistic Regression Model in PyTorch – Parts 1-3

3.5 The PyTorch API (Parts 1-2)

3.4 Automatic Differentiation in PyTorch

3.3 Model Training with Stochastic Gradient Descent (Part 1-4)

3.2 The Logistic Regression Computation Graph

3.0 Overview – Model Training in PyTorch

3.1 Using Logistic Regression for Classification (Parts 1-3)

Unit 2 Exercises

2.7 Seeing Predictive Models as Computation Graphs

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