Lectures

Lectures: Monday and Wednesday: 1:45-3:15 pm ET in Leidy Labs 10
Review: Friday: 1:45-3:15 pm ET in Wu and Chen (in Levine)
See Canvas for lecture recordings; you can also download them.

Lecture and homework dates subject to change
'Supplemental' means just for fun; not graded, not on exam

Date Assignments Topic Readings and Worksheets Quizzes

---- Review Probability and calculus (topics) Bishop 1.1-1.4, probability intro slides, MIT Probability Open Course prequiz
---- Review Linear Algebra (topics) See Resources, MLMath prequiz
---- Review python, numpy, jupyter, colab See Resources, regression in python, linear algebra

Week 0 No pods
W/Aug 31 HW0 Assignment Introduction (slides) Background: Colab Intro;

Worksheets: Python for ML, Vectorization, Array Practice

quiz and take the two prequizzes (above)

F/Sep 2

no review week0 survey

Week 1
M/Sep 5 No class: Labor Day
W/Sep 7 HW1 Assignment Local Learning and Decision Trees (slides) Decision Trees, Info Theory; Supplemental: Decision tree viz

Worksheets: K-NN, Decision trees, info gain

quiz
F/Sep 9 review survey

Week 2
M/Sep 12 HW0 due MLE/MAP and Gaussians Background: Gaussians quiz ,

pre-quiz

W/Sep 14 HW2 Assignment Linear Regression

(slides)

Bishop 3.1-3.3

Worksheets: Regression with MLE/MAP, Bernoulli MLE/MAP

quiz
F/Sep 16 review pdf slides survey

Week 3
M/Sep 19 HW1 due Overfitting and regularization; Bias-Variance Decomp Worksheet: Bias/Variance (slides) quiz
W/Sep 21 HW3 Assignment Regression Penalties Worksheets: Regression Penalties quiz
F/Sep 23 review survey

Week 4
M/Sep 26 HW2 due Logistic regression (slides) Generalized Linear Regression; Supplemental: Bishop 4.0-4.5; Worksheet:

Logistic and Kernel Regression

logistic quiz; RBF quiz
W/Sep 28 HW4 assignment Gradient Descent; KL-divergence, r.e. midterm Worksheet : K-L Divergence quiz;quiz2
F/Sep 30 review survey

Week 5 No Pods
M/Oct 3 HW3 due Random Forests, Boosting, (slides) Bishop 14.3; Supplemental: shapire tutorial

Worksheet: Boosting

quiz
W/Oct 5 SVMs (slides), kernels (slides) Bishop on large margin

Worksheet: SVMs

quiz
F/Oct 7 FALL BREAK

Week 6 No Pods
M/Oct 10 Online Learning (review slides) Worksheet: Perceptrons

Supplemental: Perceptron proof, Bishop on perceptrons

quiz
W/Oct 12 Midterm 2018 midterm and solutions; 2019 midterm and solutions and 2019 midterm comments 2022 midterm and solutions;
F/Oct 14 no review

Week 7
M/Oct 17 HW4 due HW5 Assignment Neural Nets stanford CNN course Worksheet: PyTorch,NNs, Supplemental: Gradient Descent(not graded), quiz
W/Oct 19 Neural Nets (2); Other ML courses Worksheet: CNNs quiz
F/Oct 21 Review Supplemental (for fun): Ian Goodfellow on GANS survey

Week 8
M/Oct 24 HW5 due HW6 Assignment SVD (slides),PCA (slides) SVD wikipedia; Background: matrices, Bishop, and 3blue1brown videos,PCA from Bishop

Worksheet: SVD

quiz
W/Oct 26 PCA uses,Auto-encoders (slides) Worksheets: PCA, Autoencoder

Supplemental (ungraded!): PCA/ICA and autoencoder details

quiz,quiz
F/Oct 28 Review survey

Week 9
M/Oct 31 HW6 due HW7 Assignment Project Proposal Recommender Systems (slides),

(evaluation)

Worksheet: Recommender Systems Supplemental: netflix winning paper quiz
W/Nov 2 Real world ML; Project advice,(slides) interpretation Worksheet: Evaluation Metrics, Categorical Features,

data sources, final project,sample projects

quiz
F/Nov 4 review slides survey

Week 10
M/Nov 7 Clustering (slides) and EM Bishop Ch 9

Worksheets: GMM/Kmeans, EM review Worksheet: kmeans

kmeans quiz, GMM quiz
W/Nov 9 EM, Missing Data, and Imputation (slides) Worksheet: missing data EM quiz, missing quiz
F/Nov 11 Review survey

Week 11
M/Nov 14 HW7, proposal due HW8 Assignment Naive Bayes (slides), and LDA (slides) Worksheet: NB/LDA; Supplemental: LDA intro NB quiz;LDA quiz
W/Nov 16 Belief Nets (slides), HMMs (slides) Worksheet: Belief Nets; HMM quiz
F/Nov 18

generative models, Belief Nets and friends

no survey

Week 12 No pods
M/Nov 21 HW8 due HW9 Assignment Reinforcement Learning I (slides) Worksheet: RL, Supplemental: RL-intro, MDPs, MDP-2, and MDP-3 quiz
W/Nov 23 No class but you can schedule a zoom meeting to discuss your project
F/Nov 25 No class: Thanksgiving

Week 13
M/Nov 28 Project checkpoint due Reinforcement Learning II Worksheet: RL II Supplemental:SARSA
W/Nov 30 RL: DQN and alphaZero (slides) Supplemental: RL for starcraft cicero (only available from upenn.edu quiz (just moved down from Monday)
F/Dec 3 RL recitation survey

Week 14 Presentations in pods
M/Dec 5 HW9 due AutoML, Active Learning Worksheet: AutoML, Active Learning autoML quiz active learning quiz
W/Dec 7 Interpretation and Causality Worksheet: SHAP, Worksheet: Interpreting Linear Regression Coefficients, feature importance Causality quiz
F/Dec 9 Recitation (slides) end of course survey

Week 15 No pods
M/Dec 12 Projects due Course Review (slides) (Extra slides) project participation

T/Dec 20 6:00-8:00 pm Final 2018 final and solutions; 2019 final and solutions