Lecture Schedule

  • Jan 6: Administrivia and Course Overview. Slides

  • Jan 6: A Geometric View of Linear Algebra. Notes

  • Jan 10: – contd. –

  • Jan 13: The Statistical Learning Framework. Notes

  • Jan 15: Classification: Nearest Neighbors. Notes

  • Jan 17: -contd.-

  • Jan 20: -contd.-

  • Jan 22: -contd.-

  • Jan 24: Decision Trees. Notes

  • Jan 27: No class.

  • Jan 29: -contd.-

  • Jan 31: -contd.-

  • Feb 3: -contd.-

  • Feb 5: -contd.-

  • Feb 7: No class.

  • Feb 10: Perceptron. Notes

  • Feb 12: -contd.-

  • Feb 14: -contd.-

  • Feb 17: -contd.-

  • Feb 19: Multiclass classification. Notes

  • Feb 21: -contd.-

  • Feb 24: Kernel. Notes

  • Feb 26: -contd.-

  • Feb 28: -contd.-

  • Mar 2: Finish Kernels. Start Bias and Variance Notes

  • Mar 4: Finish Bias and Variance. Start Ensemble Learning Notes

  • Mar 6: -contd.-

  • Mar 9: -contd.-

  • Mar 11: Some tips for Practical ML Slides