Applied Machine
Learning (CS 441) – Spring
2023
Instructor: Derek Hoiem
Lectures: Tues/Thurs 9:30-10:45,
1002 ECE Building
Syllabus
Lecture
Recordings
Lecture
Review Questions
and Answers
CampusWire
Discussion (code: 6897)
Canvas Submission
Textbook: Applied
Machine Learning by David Forsyth
Assignments
HW
1 – Intro to Classification and Regression (Feb 6)
HW
2 – Trees, Ensembles, and MLPs (Feb 27)
HW 3 – Application Domains and Foundation
Models (Mar 27)
HW 4 –
Pattern Discovery (Apr 17)
Final
Project (May 3)
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Class Schedule (subject to
change)
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Week |
Date |
Topic |
Link |
Reading/Notes |
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1 |
Jan 17 (Tues) |
Introduction |
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Supervised Learning Fundamentals |
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1 |
Jan 19 (Thurs) |
KNN, key concepts in ML |
AML Ch 1 |
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2 |
Jan 24 (Tues) |
Probability
and Naïve Bayes |
AML Ch 1 |
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2 |
Jan 26 (Thurs) |
Linear Least Squares and
Logistic Regression |
AML 10.1-10.2, 11 |
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3 |
Jan 31 (Tues) |
Decision Trees |
AML Ch 2 |
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3 |
Feb 2 (Thurs) |
Consolidation and Review |
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Feb 6 (Mon) |
HW 1 (Classification & Regression) due |
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4 |
Feb 7 (Tues) |
Ensembles and Random
Forests |
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AML Ch 2, Ch 12 |
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4 |
Feb 9 (Thurs) |
SVMs and SGD |
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AML Ch 2 |
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5 |
Feb 14 (Tues) |
Neural nets: MLPs, backprop |
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AML Ch 16 |
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Application Domains |
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AML Ch 16 |
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5 |
Feb 16 (Thurs) |
Deep Networks |
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6 |
Feb 21 (Tues) |
CNNs in Computer Vision |
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AML Ch
17-18 |
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6 |
Feb 23 (Thurs) |
Language Models |
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7 |
Feb 27 (Mon) |
HW 2 (Trees & MLPs) due
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7 |
Feb 28 (Tues) |
Transformers in Language
and Vision |
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7 |
Mar 2 (Thurs) |
Foundation Models: CLIP and
GPT-3 |
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8 |
Mar
7 (Tues) |
Task and Domain Adaptation |
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8 |
Mar 9 (Thurs) |
Exam 1 (on PrarieLearn) |
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9 |
Mar 11-19 |
Spring Break (no classes) |
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10 |
Mar
21 (Tues) |
Audio |
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10 |
Mar 23
(Thurs) |
Fairness
and impact on society |
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11 |
Mar 27 (Mon) |
HW 3 (Application Domains)
due |
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11 |
Mar 28 (Tues) |
Big
Data and Dataset Bias |
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Pattern Discovery |
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11 |
Mar 30 (Thurs) |
K-Means, KD-tree, LSH |
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AML Ch 8 |
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12 |
Apr 4 (Tues) |
Missing Data and EM |
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AML Ch 9 |
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12 |
Apr 6 (Thurs) |
Density estimation: MoG, Kernels, Hists |
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AML Ch 9 |
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13 |
Apr 11 (Tues) |
Data visualization: PCA and
t-SNE |
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AML Ch
11 |
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13 |
Apr 13 (Thurs) |
Topic Modeling |
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14 |
Apr 17 (Mon) |
HW 4 (Pattern Discovery)
due |
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14 |
Apr 18 (Tues) |
CCA |
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AML Ch6, Ch 19 |
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14 |
Apr 20 (Thurs) |
TBD |
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15 |
Apr 25 (Tues) |
TBD |
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16 |
Apr 27 (Thurs) |
TBD |
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16 |
May 2 (Tues) |
Looking Forward &
Requested Topics |
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16 |
May 3 (Wed) |
Final Project due (cannot be late) |
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TBA |
Final Exam (on PrairieLearn) |
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