Advanced Machine Learning - CS5824/ECE5424

Fall 2020

Instructor

Hoda Eldardiry

Description

This course will cover machine learning science, including foundations, analysis, and applications of machine learning methods.

Learning objectives

A student who completes this class should (1) have a better understanding of machine learning, and (2) be able to leverage machine learning to solve real-world problems. In particular:

Understanding of ML

  • Familiarity with a breadth of foundational machine learning concepts.
  • Awareness of the mathematical and computer science concepts underlying machine learning.
  • Acquiring background knowledge to be able to understand new machine learning methods not covered in the course.

Application of ML

  • Ability to formulate real-world problems into machine learning tasks.
  • Ability to make informed decisions about which machine learning methods are appropriate for different tasks.
  • Ability to implement standard machine learning methods without using prepackaged machine learning software.

Topics

Supervised learning, unsupervised learning, and best practices in machine learning.

Prerequisites

Experience in Python, data structures, algorithms, calculus, linear algebra, probability, and statistics.

Projects