| 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
|
|
|
|
