AI Lecture Notes and Slides

[Marc Toussaint] [other teaching material] [github sources]

Welcome to my collection of AI teaching materials. There are two parts:

• A collection of lecture notes, that are each brief and more blog style with commenting. I’m currently adding these one by one. See the list below.

• Older traditional AI lectures – see the README. This provides latex souces and pdfs for lecture slides on traditional AI, Robotics, ML, Optimization, and Maths-for-Intelligence-Systems courses.

Lecture Notes

• Entropy, Information, Cross-Entropy, and ML as Minimal Description Length
• Probabilities, Energy, Boltzmann, and Partition Function
• Robot Kinematics and Dynamics Essentials
• Splines: Cubic, Hermite, Timing-Optimal, B-Splines, Derivatives
• Quaternions, Exponential Map, and Quaternion Jacobians
• Singular Value Decomposition
• Gaussian Identities