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Machine Learning

Machine Learning

Sundays and Tusedays from 15:00 am to 16:30pm

E-Learning Center

2nd Semester 1395-1396 (Jan. 2017)

Instructor: Dr. Mohammad Reza Ahmadzadeh

Room Location: ECE  Building – B322
Internal Telephone: Ext. 5370
External Telephone: Iran: +98 (0)31 33915370
Fax: Iran: +98 (0)31 33912451
Email:

Office Hours:

I will try to be in my office on Saturdays and Mondays from 8 :00 to 9 :20 am and but I will always do my best to be available for students by appointment or any time that I am free.

Course Description:

This course covers the fundamentals of Machine Learning.

Outline:

1 Introduction 1

2 Supervised Learning 21

3 Bayesian Decision Theory 49

4 Parametric Methods 65

5 Multivariate Methods 93

6 Dimensionality Reduction 115

7 Clustering 161

8 Nonparametric Methods 185

9 Decision Trees 213

10 Linear Discrimination 239

11 Multilayer Perceptrons 267

 

12 Local Models 317

13 Kernel Machines 349

14 Graphical Models 387

15 Hidden Markov Models 417

16 Bayesian Estimation 445

17 Combining Multiple Learners 487

18 Reinforcement Learning 517

19 Design and Analysis of ML Experiments 547

 

 

Prerequisites: 

Probability Theory

Grading Policy: 

Midterm Exam ≈ 25%

HW, Comp. Assignments and projects: ≈ 30%

Final exam ≈ 45%

Time: 

Sundays and Tusedays from 15:00 am to 16:30pm

Term: 
Fall 2017
Grade: 
Graduate