| 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
|
|
|
----
|
| 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
|
|
|
|
