CSCI 374

Machine Learning

Schedule and Assignments

The following is a *tentative* schedule of topics for
our weekly meetings. In each weekly assignment, we will
itemize the readings that are required and will frequently suggest
optional readings.

**Week of 2/22**Introduction to Machine Learning; Linear Models and Perceptrons- Assignment writeup
- Required Readings

Alpaydin (4th ed.), Chapter 1: Introduction

Alpaydin (4th ed.), Chapter 2: Supervised Learning

Alpaydin (4th ed.), Chapter 10: Linear Discrimination, Sections 10.1 and 10.3 only

Alpaydin (4th ed.), Chapter 11: Perceptrons, Sections 11.1-11.4 only

Ma, J., Saul, L.K., Savage, S., and Voelker, G.M., "Identifying Suspicious URLs: An Application of Large-Scale Online Learning", ICML 2009 Proceedings of the 26th International Conference on Machine Learning, ACM, pp 681-688.

- Recommended Readings

Mitchell, Chapter 1: Introduction

Mitchell, Chapter 4: Artificial Neural Networks, Sections 4.1-4.4 only

- Turn in your assignment here.
**Week of 3/1**Naive Bayes and Logistic Regression- Assignment writeup
- Readings

Alpaydin (3rd or 4th ed.), Chapter 3, Sections 3.1-3.4

Mitchell: Generative and Discriminative Classifiers: Naive Bayes and Logistic Regression through Section 2

Mitchell (the actual textbook), Section 3.4 2, page 59 only

Witten and Frank: Section 4.2

Duda, Hart, and Stork: Section 2.1

Mitchell: Generative and Discriminative Classifiers: Naive Bayes and Logistic Regression, Section 3 through 3.1 only

- Turn in your assignment here.
**Week of 3/8**Decision Trees- Assignment writeup
- Readings

Sections 9.1-9.3

Mitchell: Chapter 3

Russell and Norvig: Section 18.3

Quinlan, "Induction of Decision Trees", Machine Learning, Vol. 1, No. 1., 1986.

Page and Ray "Skewing: An Efficient Alternative to Lookahead for Decision Tree Induction", IJCAI-03 - Turn in your assignment here.
**Week of 3/15**k-Nearest Neighbor and Social Implications of Machine Learning**Week of 3/22**Artificial Neural Networks and Deep Learning
[Note that Tuesday's meetings will be rescheduled due to Reading Period.]
**Week of 3/29**Support Vector Machines**Week of 4/5**Evaluation Methodology**Week of 4/12**Computational Learning Theory**Week of 4/19**4/21-22 are Health Days. No tutorial meetings this week. If you'd like, you might start thinking ahead to final projects.**Week of 4/26**Bias/Variance Theory and Ensemble Methods**Week of 5/3**Unsupervised Learning (including more on Deep Learning)**Week of 5/10**Student Projects: Proposals**Week of 5/17**Student Projects: Presentations