Lectures

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

Lecture and homework dates subject to change

Date Assignments Topic Readings and Worksheets Quizzes

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

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Week 0
W/Sep 1 NO CLASS! (Sorry!) take placement exam
F/Sep 3 Introduction (slides) Background: colab; Worksheets: Python for ML,array practice,Vectorization, quiz

Week 1
M/Sep 6 No class: Labor Day
W/Sep 8 Local Learning and Decision Trees (slides) decision trees, info theory; Supplemental: Decision tree viz

Worksheets: K-NN, Decision trees, info gain

quiz
F/Sep 10 MLE/MAP and Gaussians (pdf slides) Background: Gaussians quiz ,

pre-quiz , survey


Week 2
M/Sep 13 Linear Regression

(slides)

Bishop 3.1-3.3

Worksheets: Regression with MLE/MAP

quiz
W/Sep 15 Overfitting and regularization; Bias-Variance decomposition Worksheet: Bias/Variance (slides) quiz
F/Sep 17 Generalized Linear Regression;Questions quiz,survey

Week 3
M/Sep 20 Regression Penalties Worksheets: Regression Penalties quiz
W/Sep 22 Logistic regression (slides) and (Kernel regression, (slides) Supplemental: Bishop 4.0-4.5; Worksheet: Logistic and Kernel Regression quiz
F/Sep 24 Gradient Descent , Scale Invariance; KL-divergence; Review K-L Divergence quiz;quiz2; survey

Week 4
M/Sep 27 Neural Nets stanford CNN course Worksheet: PyTorch

Worksheet: Gradient Descent; NNs

quiz
W/Sep 29 Neural Nets Worksheet: CNNs quiz
F/Oct 1 more DL, DL Limitations, r.e. midterm Supplemental (for fun): Ian Goodfellow on GANS survey

Week 5
M/Oct 4 Boosting, Random Forests (slides) Bishop 14.3; Supplemental: shapire tutorial

Worksheet: Boosting

quiz
W/Oct 6 SVMs (slides) Bishop on large margin

Worksheet: SVMs

quiz
F/Oct 8 Review Session (slides) survey

Week 6 No Pods
M/Oct 11 Online Learning Worksheet: Perceptrons

Supplemental: Perceptron proof, Bishop on perceptrons

quiz
W/Oct 13 Midterm 2018 midterm and solutions; 2019 midterm and solutions and 2019 midterm comments
F/Oct 15 FALL BREAK SVD wikipedia; Background: matrices, Bishop, and 3blue1brown videos

Week 7
M/Oct 18 SVD (slides),PCA (slides) PCA from Bishop

Worksheet: SVD

quiz
W/Oct 20 PCA uses,Auto-encoders PCA, Autoencoder

Supplemental: PCA/ICA

quiz,quiz
F/Oct 22 auto-encoders, Other ML courses survey

Week 8
M/Oct 25 Clustering (slides) and EM Bishop Ch 9

Worksheet: kmeans

kmeans quiz, GMM quiz
W/Oct 27 EM, Missing Data, and Imputation (slides) Worksheet: missing data EM quiz, missing quiz
F/Oct 29 NO CLASS Worksheets: GMM/Kmeans review, EM review survey

Week 9
M/Nov 1 Recommender Systems (slides) Worksheet:Recommender Systems Supplemental: netflix winning paper quiz
W/Nov 3 Real world ML; (slides) Worksheet: Evaluation Metrics, Categorical Features,

data sources, final project

quiz
F/Nov 5 Project advice, Slides: visualization, recitation Worksheet: Interpreting Linear Regression Coefficients survey

Week 10
M/Nov 8 Naive Bayes (slides), and LDA (slides) Worksheet: NB/LDA; Supplemental: LDA intro NB quiz;LDA quiz
W/Nov 10 Belief Nets (slides), HMMs (slides) Worksheet: Belief Net; HMM quiz
F/Nov 12

generative models, Belief Nets and friends

survey

Week 11
M/Nov 15 Project proposal due Reinforcement Learning I (slides) Worksheet: RL, Supplemental: RL-intro, MDPs, MDP-2, and MDP-3 quiz
W/Nov 17 Reinforcement Learning II Worksheet: RL II quiz
F/Nov 19 RL recitation survey

Week 12 No pods
M/Nov 22 RL: DQN and alphaZero (slides) Supplemental:SARSA, RL for starcraft survey
W/Nov 24 No class but you can schedule a meeting to discuss your project (note: not during class time)
F/Nov 26 No class: Thanksgiving

Week 13
M/Nov 29 Project checkpoint due RNNs & GPT-3 Worksheet: RNN; Supplemental: GPT-3 outputs RNN quiz
W/Dec 1 AutoML, Active Learning (slides) Worksheet: AutoML, active learning autoML quiz active learning quiz
F/Dec 3 Recitation (slides) survey

Week 14 Presentations in pods
M/Dec 6 Interpretation and Causality (slides) Worksheet: SHAP Worksheet Supplemental worksheet: feature importance Causality quiz
W/Dec 8 Course Review (slides) Supplemental: tesla ML video End of Course Survey
F/Dec 10 Extra review session (slides) project participation

W/Dec 15 3:00-5:00 pm Final 2018 final and solutions; 2019 final and solutions