RIT Department of Computer Science CSCI-739-02 Introduction to Machine Learning (Fall 2018)
Instructor: Prof. Richard Zanibbi (Contact info) Office Hrs: T/Th 2:00-3:20 GOL 3551 Lectures: T/Th 3:30-4:45pm GLE 3139	Teaching Assistant: Timothy Zee (Contact info) TA Office Hrs: M/W 11:00am-12pm GOL 3650 Tutorials: (from Wk 2) Fri 1pm & 2pm Brown Hall 1110

RIT Academic Calendar

Please Note: this schedule is likely to change through the semester.

Readings will be assigned a variety of text and papers available online or through MyCourses. This will include, among other sources, The Elements of Statistical Learning (Hastie et al.) and Deep Learning (Goodfellow et al.). Readings will be announced on the "News" page (see link above).

Week	Topics	Special Events and Due Dates
1 (8/28+30)	Introduction, FIS review
2 (9/4+6)	Data, sampling, real world issues
3 (9/11+13)	Distributions, statistics review
4 (9/18+20)	Evaluating models; bias/variance	HW 1 [Data] due 9/23
5 (9/25+27)	Graphical models for classification
6 (10/2+4)	CNNs
7 (10/11)	Training deep nets	HW 2 [Graphical models] due 10/7 No class Tuesday
8 (10/16+18)	GANs
9 (10/23+25)	Network architectures
10 (10/30+11/1)	Sequence learning: Markov models	HW 3 [Nets] due 11/4
11 (11/6+8)	HMMs
12 (11/13+15)	LSTM, BLSTM	Project 1 due
13 (11/20)	GRUs	HW 4 [HMMs] due 11/18 No class Thursday
14 (11/27+29)	Reinforcement learning
15 (12/4+6)	Reinforcement, review, etc	Project 2 due
16	(Exams start - no classes)	HW 5 [RL] due 12/9
17 (12/18)	Exam	12/18, 1:30-4pm (GLE 3139 - our classroom)