COSC 6342: Machine Learning, Fall 2023

General Information


Ricardo Vilalta (


Agrawal Engineering Research (AER) Building, Room 203C.

Office Hours:

Tuesdays 10:30 AM - 11:30 AM

Class Time and Room Location:

Tuesdays 11:30 AM - 1:00 PM in Bldg: CBB, Room: 118.

No face-to-face classes on Thursdays (video lectures will be available).


(713) 743-3614


TA Information

Yasmin Farzana Michail Koumpanakis
Office Hours: Thursdays 3:00 - 4:00 PM via MS Teams Office Hours: Tuesdays 10:00 AM - Noon via MS Teams
Email: Email:

Course Description

Machine Learning is the study of how to build computer systems that learn from experience. It is a subfield of Artificial Intelligence and intersects with statistics, cognitive science, information theory, optimization, and probability theory. The course will explain how to build systems that learn and adapt using examples from real-world applications. The class will be self-contained (i.e., I will not assume any previous knowledge). The main topics include linear discriminants, neural networks, decision trees, support vector machines, unsupervised learning, and reinforcement learning.

For more information, visit the course on Canvas.


Graded Work Weight

Midterm Exams


Final Project





Dates to Remember Event
August 22 1st class
October 3 1st Midterm Exam
November 21 No Class; Thanksgiving Holiday
November 28 2nd Midterm Exam
December 6 Final Project Due (midnight)

Note: This course has no final exam.


Dates Topic
August 22 Introduction to Machine Learning and Supervised Learning
August 29 Linear Regression
September 5 Linear Classification
September 12 Basis Expansions and Regularization
September 19 Decision Trees and Related Methods
September 26 Model Assessment and Selection
October 3 1st Midterm Exam
October 10 Neural Networks
October 17 Random Forests and Boosting
October 24 Support Vector Machines
October 31 Unsupervised Learning
November 7 Reinforcement Learning
November 14 Learning Theory
November 21 Thanksgiving Holiday - No Class
November 28 2nd Midterm Exam
December 6 Final Project Due (midnight)

Additional Information

For more information, visit the course on Canvas.

Please click here for a complete description of the required information pertaining to courses offered at UH this semester.