Computer Science 394

Seminar: Machine Learning
Spring 2019
Thomas VanDrunen



Meeting time: MWF 12:55am-2:05pm.
Meeting place: Meyer 131

Office hours: MWF 3:30-4:30 pm; Th 9:00-10:30 am, 11:00-11:30, and 1:15-3:15 pm.
Contact: 163 Science; 752-5692; Thomas.VanDrunen@wheaton.edu
http://cs.wheaton.edu/~tvandrun/cs345


Syllabus
Citation policy for projects



Final exam: Thur, May 9, 1:30pm-3:30pm


Moon's dayWoden' s dayFrigga's day

Jan 14

Introduction

Learn Python
Read pg 1-12

Jan 16

Basic concepts and terminology

Jan 18

Probability and statistics background
Slides

Read Section 1.2, pg 12-32

Jan 21

NO CLASS

Jan 23

Probability densities; expectation
Slides

Do Ex 1.(3, 5, 6), pg 58-59

Jan 25

Bayesian probabilities
Slides

Read 1.(3&4) and 2.5 FOR Fri 2/1

Jan 28

Lab: Becoming acquainted with the libraries

Lab activity

Jan 30

No class: College closed for cold weather

Feb 1

Various small topics
Slides

Feb 4

Lab: From histograms to Gaussians

Lab activity

Feb 6

Kernel densities and KNN

Read 2.3.9 (pg 110-113) and 9.2 (430-439)
Project: KNN Due Feb 20

Feb 8

Fitting Gaussians, EM

Feb 11

Lab: Gaussian EM

Lab activity

Feb 13

Continuing Gaussian EM lab...

Read 3.(1-3), (pg 137-161)

Feb 15

Linear regression

Feb 18

NO CLASS

Feb 20

Linear regression

Feb 22

Lab: Linear regression

Lab activity

Feb 25

Review

Feb 27

Test

Read Ch 5 intro and Section 5.1 (pg 225-232)

Mar 1

Neural networks

Mar 4

Lab: Neural nets

Lab activity

Mar 6

Multilayer perceptron training

Mar 8

Multilayer perceptron training
Slides

Project: MLP Due March 29

Mar 11

NO CLASS

Mar 13

NO CLASS

Mar 15

NO CLASS

Mar 18

Lab: Tensor flow

Lab activity

Mar 20

Continue lab

Advanced lab activity

Mar 22

Wrap-up ANNs
Slides

Mar 25

Support vector machines
Slides

Mar 27

Lab: SVMs

Lab activity
Read Ch 7 intro and Section 7.1 (pg 325-345)

Mar 29

The math of SVMs

Apr 1

Lab: Applying SVMs

Lab activity

Apr 3

Implementing SVMs from (almost) scratch
Slides

Project: SVMs Due Apr 26

Apr 5

Lab...

Read Ch 12 intro and 12.1-12.2.2 (pg 559-580)

Apr 8

Principal component analysis concepts
Slides

Apr 10

No class: family illness

Apr 12

Lab: PCA

Lab activity

Apr 15

Algorithms for PCA; intro to genetic algorithms

Project: PCA, due May 3

Apr 17

Lab: Reinforcement learning

Lab activity
Readings, responses, and reflections

Apr 19

NO CLASS

Apr 22

Ethics: Bias in algorithms

Apr 24

Ethics: Various topics

Apr 26

Ethics: Learning and obscurity

Apr 29

Ethics: Machine learning and healthcare

May 1

Ethics: Ethical algorithms

May 3

Review and other final business