In-Class Activities

• Activity 1: Introduction

• Activity 2: kNN, Math, NumPy

  • Live notebook

• Activity 3: Linear regression

• Activity 4: Implementing linear regression

  • Live notebook

• Activity 5: Gradient descent

• Activity 6: Holdout and model evaluation

  • Live notebook

• Activity 7, Part 1: Regularization

• Activity 7, Part 2: Polynomial Features and Ridge Regression

  • Live notebook

• Activity 8: Classification predictions and gradients

  • Live notebook

• Activity 9: Classification Metrics

• Activity 10: ROC Curves

• Activity 11: Fairness

  • Live notebook

• Activity 12: Trees and Bagging

• Activity 13: Boosting and Projects

• Activity 14: Bootstrapping and Variance

• Activity 15: Neural Networks Forward Predictions

  • Live activity

  • Notebook

  • Live notebook

• Activity 16: Neural Networks II

  • Live notebook

• Activity 17: Neural Networks III

  • Colab

• Activity 18: Unsupervised Learning I

• Activity 19: Unsupervised Learning II

• Activity 23: Language Models