CSE/STAT 416, Summer 2019: Introduction to Machine Learning

Calendar

Note: This is a rough sketch of the quarter that is likely to change. We can accurately predict the past, but predicting the future is hard!

Day
Topic
Materials
References
Assignments

Case Study: Regression

Week 1: Introduction / Regression
Lecture 1
(Mon, June 24)
Linear Regression
    Optional:
  • [Schafer] Python Review
  • [ESL] Section 1, 2.3.1
Lecture 2
(Wed, June 26)
Assessing Performance
Bias + Variance Tradeoff
    Optional:
  • [ESL] Section 2.3.1, 7.1-7.4
Section 1
(Thur, June 27)
Course Infrastructure / Pandas
Week 2: Assessing Performance
Lecture 3
(Mon, July 01)
Regularization: Ridge
    Optional:
  • [ESL] Section 3.1-3.2, 3.4.1
  • [ESL] Section 7.1-7.4
Lecture 4
(Wed, July 03)
Regularization: LASSO, Feature selection
    Optional:
  • [ESL] Section 2.9, 5.5.2, 7.2
  • [ESL] Section 3.4.2, 7.10
Section 2
(Thur, July 04)
4th of July. No class.

Case Study: Classification

Week 3: Classification
Lecture 5
(Mon, July 08)
Classification
    Optional:
  • [ESL] Section 1, 2.3.1, 4.1-4.2
Lecture 6
(Wed, July 10)
MLE / Logistic Regression
    Optional:
  • [ESL] Section 4.4.1-4.4.4, 9.1.2, 7.5-7.6
Section 3
(Thur, July 11)
Classification / Logistic Regression
  • Handout : pdf
  • Solutions : pdf
Week 4: Trees
Lecture 7
(Mon, July 15)
Decision Trees
Lecture 8
(Wed, July 17)
Ensembles Methods
Section 4
(Thur, July 18)
Trees and Ensemble Models
  • Handout : pdf
  • Solutions : pdf

Case Study: Clustering and Similarity

Week 5: Non-Parametric Methods
Lecture 9
(Mon, July 22)
Precisions+Recall / kNN
Lecture 10
(Wed, July 24)
Kernel Methods
Locality Sensitive Hashing
Section 5
(Thur, July 25)
Kaggle Setup
Precision/Recall + Local Methods
  • Handout : pdf
  • Solutions : pdf
Week 6: Clustering
Lecture 11
(Mon, July 29)
Clustering
Lecture 12
(Wed, July 31)
Hierarchical Clustering
  • Slides : pdf
  • Missing Data : pdf
    Optional:
  • [ESL] Section 14.3.12, 9.6
Section 6
(Thur, Aug 01)
Numpy and Clustering
  • Handout : pdf
  • Solution : pdf
  • Numpy Demo : pdf
  • Numpy Demo Solution : pdf

Case Study: Deep Learning

Week 7: Deep Learning
Lecture 13
(Mon, Aug 05)
Neural Networks
Lecture 14
(Wed, Aug 07)
Deep Learning
Convolutional Neural Networks
Section 7
(Thur, Aug 08)
Deep Learning
  • Handout : pdf
  • Solution : pdf

Case Study: Recommender Systems

Week 8: Recommender Systems
Lecture 15
(Mon, Aug 12)
PCA / Recommender Systems Intro
Lecture 16
(Wed, Aug 14)
Recommender Systems / Matrix Factorization
Section 8
(Thur, Aug 15)
PCA
Recommender Systems
Final Exam Review
  • Handout : pdf
  • Solution : pdf
Week 9: Wrap Up / Final Exam
Lecture 17
(Mon, Aug 19)
Online Learning / Course Wrap Up
  • Online Learning Slides : pdf
  • Course Wrap-up Slides : pdf
Lecture 18
(Wed, Aug 21)
Final Exam (in class)
Section 9
(Thur, Aug 22)
No section