Spring 2020

Below are the the topics we aim to cover but time and the order might change.

Week Tuesday Thursday Thursday Section References (optional) Assignment
1. March 30 Intro to Machine Learning
slides		 Linear Regression, Assessing Performance
slides, colab		 Pandas
exercises, solutions, slides		 [PyDS] Intro, Linear Regression; [ESL] Section 1, 2.3.1 HW0 due April 8th
2. April 6 Bias/Variance Trade-off
slides		 Regularization, Ridge Regression
slides,colab		 Gradient Descent
colab,
slides,
calculus		 [PyDS] Model Selection, Regularization; [ESL] Section 7.1-7.4, 3.4.1 HW1 due April 15th
3. April 13 Feature Selection, Lasso Regression
slides,colab		 Classification Overview
slides		 Bias Var & Ridge Lasso
slides
colab		 [ESL] Section 3.4.2-3.4.3 HW2 due April 22th
4. April 20 Evaluation Metrics, Logistic Regression
slides		 Naive Bayes
slides		 Logistic Regression colab [ESL] Section 4.1, 4.4.1-4.4.4, 9.1.2, 9.2.5, 6.6.3, ROC/PR Curves, Scikit-Learn Reference, [PyDS] Naive Bayes HW3 due April 30th
5. April 27 Decision Trees
slides		 Ensemble Methods
slides		 Random Forest 😆
Random Forest Slides, Gini Impurity Slides, Random Forest colab, Titanic colab		 [ESL] Section 9.2.1-9.2.3,15.1-15.3.2, 10.1,[PyDS] HW4 due May 7th
6. May 5 Nearest Neighbors
slides		 Kernel Methods
slides		 Method Review
Colab , Topics Sheet, Variable Encoding Colab		 [ESL] Section 13.3, Scikit-Learn Reference, CV for groups and time series HW5 due May 14th
7. May 11 Neural Networks
slides		 Convolutional Neural Networks, Transfer Learning
slides		 Keras & CNN
slides,
blog slides,
cnn_notebook,
nn_notebook		 Neural Networks Intro, CNN Intro, Deep Forward Networks, Convolutional Neural Networks HW6 due May 21st
8. May 18 K-means
slides		 Assessment, Hierarchical Clustering
slides, Dendrogram Details		 Unsupervised Learning :)
colab		 [ESL] Section 14.3.6, 14.3.7, 14.3.12 HW7 due May 28th
9. May 25 Dimensionality Reduction
PCA
slides		 NMF
slides		 PCA in higher dimensions 😎
slides!
pca_colab!
nmf_colab!
pca_and_nmf		 PCA, PCA Math
NMF, NMF: Recommender Systems, NMF: Learning by Parts		 HW8 due June 4th
10. June 1 Nonlinear Embeddings
slides		 Guest Lecture by Bernease Herman: Ethics in Machine Learning     Â