Introduction to Machine Learning

10-601, Spring 2017
School of Computer Science
Carnegie Mellon University

Important Notes

This schedule is tentative and subject to change. Please check back often.

Note that the times below are for students in all sections unless otherwise noted.

Tentative Recitation Schedule

Topic Date Time Location
1. Math Background Thu, 26-Jan Sections A & C: 6:30pm. Section B: 7:15pm. PH 100
2. Computer Science Background Tue, 31-Jan 6:30pm PH 100
3. Autolab / Python / Octave Thu, 2-Feb 6:30pm PH 100
4. HW2: MLE & Naive Bayes Tue, 7-Feb 6:30pm PH 100
5. HW3: Linear & Logistic Regression Thu, 16-Feb 6:30pm PH 100
6. HW4: SVMs & Kernels Thu, 23-Feb 6:30pm PH 100
7. Midterm Thu, 2-Mar 6:30pm PH 100
8. HW6: Unsupervised Learning Tue, 28-Mar 6:30pm PH 100
9. Midterm Solutions Tue, 4-Apr 6:30pm PH 100
10. HW7: Deep Learning Thu, 6-Apr 6:30pm PH 100
11. HW8: Graphical Models Tue, 18-Apr 6:30pm PH 100
12. HW9: Real Data Thu, 27-Apr 6:30pm PH 100
13. Mock Final Thu, 4-May 6:30pm PH 100