Welcome to CSE/STAT 416: Introduction to Machine Learning! ­čÄë

Registration

Do not email the course staff or instructor requesting an add-code for the course. The course staff do not have any add-codes. Please see the Registration FAQ for answers to common registration questions.

Announcements

May 31

End of Quarter Details & A Lot of Grades Posted

May 26

Bob Bandes CSE TA Award Nominations Open for All Quarters

May 26

Melissa's Office Hours Location

All Announcements

This Week (at a glance)

Wednesday (06/07)

  • Review Session (TBD)
  • ­čžá Learning Reflection 9. Due Wednesday (06/07) @ 11:59 pm

Thursday (06/08)

  • Final Exam from 8:30 - 10:20 am in Condon 109

Friday (06/09)

  • Checkpoint 18 due (no lates)
  • Last day to turn in any outstanding late work (LR9, remaining Checkpoints)

Calendar

Info

This is a rough sketch of the quarter and things are subject to change. We can accurately predict the past, but predicting the future is hard!

Lessons

Anything listed in the “Lesson” materials for a day should be done before attending class that day. We recommend doing all the slides before the “Pause and Think” slide. Each class session will start by reviewing what was in the Lesson and then most time will be spent on working on practice problems in the Lessons. See the syllabus for more info!

Topic Homeworks Learning Reflections
Module 0 - Introduction / Regression
Mon 03/27
LES 00 Regression

Note: Normally there is are pre-class materials that you should complete before attending class. For the first day there are none! You should complete the Checkpoint after class (due before the next class).

Note (2): The CSE/STAT 416 Training links for today are extremely useful resources to make sure you are prepared for the class. The course will be in Python, so Resources 1 and 2 will be very helpful if you are less familiar with the language. Resource 3 covers the mathematical background we expect students to be comfortable with in the course. You are expected to complete these trainings, but they are not factored into your grade. We encourage you to work on them now before assignments are released.

pre-class: None megathread
in-class: pdf annotated pptx
post-class: checkpoint
resources:
Videos
Extra resources
Out
LR0
Due 11:59 pm
Tue 03/28
Wed 03/29
LES 01 Assessing Performance; Bias + Variance Tradeoff
Out
HW0
House Prices
Due 11:59 pm
Thu 03/30
SEC 00 Course Infrastructure; Pandas
resources: handout
Fri 03/31
Module 1 - Assessing Performance
Mon 04/03
LES 02 Regularization: Ridge
Out
LR1
Due 11:59 pm
Tue 04/04
Wed 04/05
LES 03 Regularization: LASSO, Feature selection
Out
HW1
Ridge and LASSO
Due 11:59 pm
Thu 04/06
SEC 01 Ridge and LASSO; Code
resources: handout
Fri 04/07
Module 2 - Classification
Mon 04/10
LES 04 Classification
Out
LR2
Due 11:59 pm
Tue 04/11
Wed 04/12
LES 05 MLE / Logistic Regression
Out
HW2
Sentiment Analysis with Logistic Regression
Due 11:59 pm
Thu 04/13
SEC 02 Classification ; Logistic Regression
resources: handout
Fri 04/14
Module 3 - Societal Impact, Bias, and Fairness
Mon 04/17
LES 06 Bias and Fairness
Out
LR3
Due 11:59 pm
Tue 04/18
Wed 04/19
LES 07 Fairness and Tradeoffs ; Recap
pre-class: none
in-class: pdf annotated pptx
post-class: checkpoint megathread
Advanced resources
Thu 04/20
SEC 03 Midterm Review
resources: handout
Fri 04/21
Out
EXAM
Take-Home Midterm
Due 11:59 pm
Module 4 - Trees/Ensemble Methods
Mon 04/24
LES 08 Naive Bayes / Decision Trees
Out
LR4
Due 11:59 pm
Tue 04/25
Wed 04/26
LES 09 Ensemble Methods
Out
HW3
Loan Safety with Decision Trees
Due 11:59 pm
Thu 04/27
SEC 04 Trees and Ensemble Methods
Fri 04/28
Module 5 - Deep Learning
Mon 05/01
LES 10 Neural Networks
Out
LR5
Due 11:59 pm
Tue 05/02
Wed 05/03
LES 11 Deep Learning; Convolutional Neural Networks
Out
HW4
Deep Learning with PyTorch
Due 11:59 pm
Thu 05/04
SEC 05 Deep Learning
Fri 05/05
Module 6 - Non-Parametric Methods
Mon 05/08
LES 12 Precision + Recall / kNN
Out
LR6
Due 11:59 pm
Tue 05/09
Wed 05/10
LES 13 Kernel Methods; Locality Sensitive Hashing
Out
HW5
ML Practice on Kaggle
Due 11:59 pm
Thu 05/11
SEC 06 Kaggle Setup
Fri 05/12
Module 7 - Clustering
Mon 05/15
LES 14 Clustering
Out
LR7
Due 11:59 pm
Tue 05/16
Wed 05/17
LES 15 Hierarchical Clustering
Out
HW6
k-means with Text Data
Due 11:59 pm
Thu 05/18
SEC 07 Numpy ; Variable Encoding ; Clustering
Fri 05/19
Module 8 - Recommender Systems
Mon 05/22
LES 16 PCA / Recommender Systems Intro
Out
LR8
Due 11:59 pm
Tue 05/23
Wed 05/24
LES 17 Recommender Systems / Matrix Factorization
Out
HW7
Tweet Topic Modelling
Due 11:59 pm
Thu 05/25
SEC 08 PCA ; Recommender Systems
Fri 05/26
Module 9 - Course Wrap Up
Mon 05/29
HOLIDAY Memorial Day
Tue 05/30
Out
LR9
Due 11:59 pm
Wed 05/31
LES 18 Course Wrap Up; Next Steps; Generative AI
Thu 06/01
SEC 09 Final Review
Fri 06/02
Module 10 - Finals Week
Mon 06/05
Tue 06/06
Wed 06/07
Thu 06/08 Final Exam: 8:30 - 10:20 am in CDH 109
EXAM
Final Exam
At 8:30 am
Fri 06/09 Last day to submit late work on remaining available assignments and existing regrade requests