CS 445/545: Machine Learning

Instructor: Ehsan Aryafar
Picture Course Description and Objectives:

This course provides a broad introduction to techniques for building computer systems that learn from experience; conceptual grounding and practical experience with several learning systems; and grounding for advanced study in statistical learning methods, and for work with adaptive technologies used in speech and image processing, robotic planning and control, diagnostic systems, complex system modeling, and iterative optimization. Students gain practical experience implementing and evaluating systems applied to pattern recognition, prediction, and optimization problems.


Prerequisites and Computer Access Requirements:
We will use Python to create, train, and test ML models. We will provide a brief intro to Python and the libraries that we will use in the course but students are expected to be already familiar with a programming language to quickly pick up and code in Python. Students are expected to have access to a laptop or desktop. For computer specifications, please consult the laptop policy adopted by the department. Note that a desktop with these configurations is also fine. We will provide instructions on how to setup Python and the associated libraries.

Textbook:
Required and Reference Textbooks: The math and programming concepts of the course follow these books:
Hastie, Tibshirani, Friedman, “Elements of Statistical Learning”.
Raschka, “Python Machine Learning”, 2015.

Syllabus:
Course syllabus can be downloaded at the following link.

Course Structure and Grading:
Class Participation: 10%
Homework: 60%
Exam: 30%

Participation: Students who will take the class asynchronously need to let the instructor know. Students who attend regularly but miss more than three sessions need to let the instructor know of why they have missed the class. Students should treat each other with respect at all times.
Assignments: There will be four homework assignments containing math and programming questions. Assognments will be given in JupyterLabs and should be returned in the same format.
Exam: There will be a single exam. The exam will be based on the topics (lectures) that are covered in the class. The exam will be open-book and open-notes.

Sexual harassment, sexual assault, dating/domestic violence and stalking:
Portland State is committed to providing an environment free of all forms of prohibited discrimination and sexual harassment (sexual assault, domestic and dating violence, and gender or sex-based harassment and stalking). If you have experienced any form of gender or sex-based discrimination or sexual harassment, know that help and support are available. PSU has staff members trained to support survivors in navigating campus life, accessing health and counseling services, providing academic and on-housing accommodations, helping with legal protective orders, and more. Information about PSU’s support services on campus, including confidential services and reporting options, can be found on PSU’s Sexual Misconduct Prevention and Response website at: http://www.pdx.edu/sexual-assault/get-help or you may call a confidential IPV Advocate at 503-725-5672. You may report any incident of discrimination or discriminatory harassment, including sexual harassment, to either the Office of Equity and Compliance or the Office of the Dean of Student Life.

Please be aware that all PSU faculty members and instructors are required to report information of an incident that may constitute prohibited discrimination, including sexual harassment and sexual violence. This means that if you tell me about a situation of sexual harassment or sexual violence that may have violated university policy or student code of conduct, I have to share the information with my supervisor, the University’s Title IX Coordinator or the Office of the Dean of Student Life. For more information about Title IX please complete the required student module Creating a Safe Campus in your D2L.

Disability accommodations:
PSU values diversity and inclusion; we are committed to fostering mutual respect and full participation for all students. My goal is to create a learning environment that is equitable, useable, inclusive, and welcoming. If any aspects of instruction or course design result in barriers to your inclusion or learning, please notify me. The Disability Resource Center (DRC) provides reasonable accommodations for students who encounter barriers in the learning environment.

If you have, or think you may have, a disability that may affect your work in this class and feel you need accommodations, contact the Disability Resource Center to schedule an appointment and initiate a conversation about reasonable accommodations. The DRC is located in 116 Smith Memorial Student Union, 503-725-4150, drc@pdx.edu, https://www.pdx.edu/drc.
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