- Syllabus (pdf), tentative course schedule (pdf), and prerequisite quiz (ungraded)
- Brightspace (Grades) - For the first time logging into Piazza and Gradescope, please click the links in Brightspace under “Content” and then under the module “Piazza, Gradescope, and Circuit Links”. This will help link your Purdue account with these external learning tools. After the first time, you can just use the links below.
- Piazza (Announcements and discussion)
- Gradescope (Online quizzes, exams, and assignment submission)
- Google Colab (Online computing environment including GPUs)
The bracketed acronym is used for referencing these books.
- [DL] Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, 2016. http://www.deeplearningbook.org
- [ML] Machine Learning: A Probabilistic Perspective by Kevin P. Murphy, 2012. https://ebookcentral.proquest.com/lib/purdue/detail.action?docID=3339490
- [PY] Python Data Science Handbook by Jake VanderPlas, 2016. https://jakevdp.github.io/PythonDataScienceHandbook/
Lecture content by week
- Week 1 - Introduction to artificial intelligence
- Week 2 - PCA and linear algebra
- Week 3 - Introduction to machine learning
- Week 4 - Linear models and gradient descent
- Week 5 - Basics of deep learning