Schedule

CIS5200 Machine Learning

Jan 12

Lecture Introduction & Course Overview: Slides, Notes

Instructor: Eric and Surbhi

HW 0 out: HW 0 Assignment

Jan 17

Lecture Binary Classification, Perceptron: Slides, Notes

Instructor: Surbhi

Jan 19

Lecture Linear Regression, Logistic Regression: Slides, Notes

Instructor: Surbhi

Jan 20

HW 0 due

Jan 23

HW 1 out: HW 1 Assignment

Jan 24

Lecture Clustering, K-Means: Risk Reading (Section 1.2), K-Means Reading

Instructor: Eric

Jan 26

Lecture Gaussian Mixture Models, EM: Mixture of Gaussian from K-Means Reading (same reading as Jan 24), Mixtures of Gaussians from log likelihood and the EM algorithm Reading, General EM algorithm Reading (Sections 1+2)

Instructor: Eric

Jan 31

Lecture PCA, ICA: Principal Components Analysis (PCA) and Dimensionality Reduction, Independent Components Analysis (ICA)

Instructor: Eric

Feb 2

Lecture Linear Programs, Duality, Quadratic Programs: Duality, LP, QP notes (Section 3.3)

Instructor: Eric

Feb 3

HW 1 due

Feb 6

HW 2 out: HW 2 Assignment

Feb 7

Lecture Support Vector Machines (SVMs): Slides, Notes

Instructor: Surbhi

Feb 9

Lecture Kernel Methods: Slides, Notes

Instructor: Surbhi

Feb 14

Lecture Gradient Descent: Slides, Notes

Instructor: Surbhi

Feb 16

Lecture Gradient Descent (cont.): Slides, Notes, Optional Material (PGD and SGD (Sections 3.3, 3.4))

Instructor: Eric

Feb 17

HW 2 due

Feb 21

Lecture HMMs: HMM Reading

Instructor: Eric

Feb 23

Midterm

Feb 28

Lecture MCMC: Notes

Instructor: Eric

Mar 2

Lecture PAC Learning: Slides, Notes

Instructor: Surbhi

Mar 7

Spring Break

Mar 9

Spring Break

Mar 14

Lecture VC Theory: Slides Notes

Instructor: Surbhi

Mar 16

Lecture Bias/Variance Tradeoff: Slides Notes

Instructor: Surbhi

Mar 19

HW 3 out: HW 3 Assignment

Mar 21

Lecture Decision Trees: Notes

Instructor: Eric

Mar 23

Lecture Bagging, Random Forests: Bagging and Random Forests Reading

Instructor: Eric

Mar 28

Lecture Boosting: Slides Notes

Instructor: Surbhi

Mar 30

Lecture Active Learning: Slides Notes

Instructor: Surbhi

Apr 1

HW 3 due

Apr 4

Lecture Neural Networks (1): Notes Neural Networks reading (SB Chapter 20)

Instructor: Eric

Apr 4

HW 4 Written out: HW 4 Written Assignment

Apr 6

Lecture Neural Networks (2): Notes Automatic differentiation

Instructor: Eric

Apr 9

HW 4 Programming out: HW 4 Programming Assignment

Apr 11

Lecture Online Learning: Slides Notes

Instructor: Surbhi

Apr 13

Lecture Reinforcement Learning: Notes

Instructor: Eric and Surbhi

Apr 14

HW 4 Written due

Apr 17

HW 5 out: HW 5 Assignment

Apr 18

Lecture Guest Lecture: NLP/Transformers: Slides

Instructor: Cyril Zhang, Microsoft Research NYC

Apr 19

HW 4 Programming due

Apr 20

Lecture Guest Lecture: Vision/Robotics: Slides

Instructor: Dinesh Jayaraman, UPenn

Apr 25

Lecture Introspection: Challenges and Risks of ML: Slides

Instructor: Eric and Surbhi

Apr 26

HW 5 due