CSEP546: Machine Learning

University of Washington School of Computer Science & Engineering

CSEP 546 - Machine Learning - Autumn 2019
Tuesdays 6:30-9:20pm buildings:
- Allen Center, room 305
- Microsoft Building 99, room 1915

Instructor: Geoff Hulten

Office Hours: Email and discussion board any time

TA	Office Hours
Alon Milchgrub	Tues: 5:30 - 6:30 Location: CSE 674
Andrew Wei	Tues: 4:30 - 6:20 Location: CSE 007

Archive of lecture videos

Assignments posted on canvas. You can find an archive of them here.

Schedule

Week	Topics	Video
1	Introduction Overview of Machine Learning Basics of Evaluating Models Logistic Regression	Overview of Machine Learning Basics of Evaluating Models Logistic Regression
2	Feature Engineering (Text) ROC Curves and Operating Points	Feature Engineering (Text) ROC Curves and Operating Points Extra Content: Feature Engineering & Bag of Words
3	Bounds and Comparing Models Naive Bayes Implementing with Machine Learning	Bounds and Comparing Models Naive Bayes Implementing with Machine Learning Extra Content: Approaching the Kaggle Assignment
4	Decision Trees Defining Success with ML Systems Intelligent User Experiences	Decision Trees Defining Success with ML Systems Intelligent User Experiences
5	Overfitting and Underfitting Design Pattern - Adversarial Learning Ensembles 1 - Bagging and Randomforests	Overfitting and Underfitting Design Pattern - Adversarial Learning Ensembles 1 - Bagging and Randomforests Extra Content: Midterm Review
6	Ensembles 2 - Boosting Basics of Computer Vision Clustering and Instance Based Learning	Ensembes 2 - Boosting Basics of Computer Vision Clustering and Instance Based Learning
7	Neural Networks Design Pattern - Corpus Centric	Neural Networks Design Pattern - Corpus Centric
8	Ensembles 3 - Stacking and Intelligence Architectures Neural Network Architectures	Ensembles 3 - Stacking and Intelligence Architectures Neural Network Architectures Extra Content: Installing PyTorch on Visual Studio Extra Content: Simple PyTorch Neural Network
9	Design Pattern - Ranking Reinforcement Learning	Design Pattern - Ranking Reinforcement Learning
10	Orchestrating Intelligent Systems Other Important Machine Learning Algorithms Review of the Course Part II	Orchestrating Intelligent Systems Overview of Other ML Techniques Extra Content: Review of the Course Part II

Note: Schedule subject to change.

Textbooks

Machine Learning
by: Tom Mitchell

Building Intelligent Systems
by: Geoff Hulten
All royalties will be donated

Course Administration and Policies

Assignments will be done individually. You may discuss the subject matter with other students in the class, but all final answers must be your own work. You are expected to maintain the utmost level of academic integrity in the course.

There will be an online final.