# Machine Learning & Discovery

## ECS 271

## Fall 2022

## Contact Information

Instructor:
Hamed Pirsiavash, Kemper Hall 3061, hpirsiav AT ucdavis DOT edu, Office hours: Thursdays at 2-3pm on Zoom.
TA:
Parsa Nooralinejad, pnooralinejadeslamloo AT ucdavis DOT edu, Office hours: Mondays and Friday 3-4:30, Location: TBD
## Grading

There will be 3-4 homeworks: 70% total.
There will be a major final project: 30%.
There "may" be a final exam. If so the grade will be distributed differently: homework: 60%, project: 30%, exam: 10%
Each student has five penalty-free late days for the whole semester that can be used for the homework only. Any extra late day will be penalized.

The homeworks will involve both written problem sets and MATLAB or Python coding.

## Textbook

**1: A Course in Machine Learning** by Hal Daume III ** (Main)**
**2: Machine Learning: A Probabilistic Perspective** by Kevin Murphy
**3: Pattern Recognition and Machine Learning** by Christopher M. Bishop
## Other Resources

**Machine learning course by Andrew Ng**
**Decision trees by Martial Hebert**
**CNNs by Svetlana Lazebnik**
## Tentative Syllabus

09/22 : Introduction (slides)
09/27 : Decision trees (slides)
09/29 : Decision trees
10/04 : K-nearest neighbors (slides)
10/06 : Perceptron (slides)
10/11 : Linear models (slides)
10/13 : No Class
10/18 : Linear models
10/20 : Linear models
10/25 : Neural networks (slides)
10/27 : Neural networks
11/01 : Convolutional neural networks and deep learning (slides) (slides)
11/03 : Convolutional neural networks and deep learning
11/08 : Support Vector Machines (slides included in linear models)
11/10 : Support Vector Machines
11/15 : Clustering (slides)
11/17 : Dimensionality reduction (slides)
11/22 : Probabilistic modeling (slides)
11/24 : Thanksgiving Holiday
11/29 : Self-supervised deep learning (slides)
12/01 : Generative adversarial networks (GANs) (slides)
## Homework

Homework 1, due 10/13/2022 at 11:59pm: pdf, tex, Matlab code, Python code, data, mydefs.sty, notes.sty
Homework 2, due 11/14/2022 at 11:59pm: pdf, tex
Homework 3, due 12/01/2022 at 11:59pm: pdf, tex