Lecture Schedule

• Jan 4: The landscape of machine learning Slides

• Jan 6:

  • Course logistics Notes

  • Nearest neighbor classification Slides

• Jan 8:

  • Nearest neighbor classification (contd.)

  • Statistical learning framework Notes

• Jan 11: - contd. -

• Jan 13: - contd. -

• Jan 15: Linear regression Annotated slides

• Jan 18: Holiday

• Jan 20: Linear regression (contd.) Annotated slides

• Jan 22: Logistic regression Annotated slides

• Jan 25: Convex Optimization Notes

• Jan 27: - contd. -

• Jan 29: - contd. -

• Feb 1: - contd. -

• Feb 3: - contd. -

• Feb 5: Perceptron Slides

• Feb 8: Support vector machine Slides

• Feb 10: - contd. -

• Feb 12: Multiclass classification Annotated slides

• Feb 15: Holiday

• Feb 17: Decision tree Slides

• Feb 19: - contd. -

• Feb 22: Kernel methods Annotated slides

• Feb 24: - contd. -

• Feb 26: - contd. - Notes

• Mar 1: Neural nets Annotated slides

• Mar 3: - contd. -

• Mar 5: Generalization theory Notes

• Mar 8: - contd. -

• Mar 10: - contd. -

• Mar 12: - contd. -