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. -