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Notes

• Batch, Group, and Layer Normalization
• Building a Machine Learning Model
• Exploding and Vanishing Gradients
• Gradient Descent
• Information Theory
• Learning to Rank
• Model Performance and Compression
• Norms
• Pointer Types in Rust
• Recommender Models
• Regularization
• Statistical Hypothesis Testing