ECE 47300, Intro. to Artificial Intelligence (Spring 2023)

Optional textbooks

The bracketed acronym is used for referencing these books.

  1. [DL] Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, 2016. http://www.deeplearningbook.org
  2. [ML] Machine Learning: A Probabilistic Perspective by Kevin P. Murphy, 2012. https://ebookcentral.proquest.com/lib/purdue/detail.action?docID=3339490
  3. [PY] Python Data Science Handbook by Jake VanderPlas, 2016. https://jakevdp.github.io/PythonDataScienceHandbook/

Lecture content by week

  1. Week 1 - Introduction to artificial intelligence
    • Tuesday: Introduction to AI. See syllabus, course schedule, and course project links above.
    • Thursday: Overview of AI; Started PCA and linear algebra (see notes below)
  2. Week 2 - PCA and linear algebra
  3. Week 3 - Introduction to machine learning
  4. Week 4 - Linear models and gradient descent
  5. Week 5 - Basics of deep learning