## Mathematics for AI (AI503, Fall 2021)This course is to study mathematical skills useful for graduate students working in the area of artificial intelligence and machine learning. ## AnnouncementWe will use two textbooks, Textbook A and Textbook B. Acknowledgement: A half of lectures slides would be based upon what made by Yung Yi (link) The first homework is uploaded (due date: September 28th). The second homework is uploaded (due date: October 19th). The third homework is uploaded (due date: November 9th). The fourth homework is uploaded (due date: November 25th). The fifth homework is uploaded (due date: December 9th).
## ScheduleLecture 0: Introduction to AI503 Lecture 2: Continuous Optimization (Chapter 7 of Textbook A) Lecture 4: Linear Regression (Chapter 9 of Textbook A) Lecture 5: PCA (Chapter 10 of Textbook A) Lecture 6: GMM (Chapter 11 of Textbook A) Lecture 7: SVM (Chapter 12 of Textbook A) Lecture 9: Random Walks and Markov Chains (Chapter 4 of Textbook B) Lecture 10: VC-Dimension (Chapter 5 of Textbook B) Lecture 11: Streaming, Sketching, and Sampling (Chapter 6 of Textbook B) Lecture 12: Clustering (Chapter 7 of Textbook B) Lecture 13: Random Graphs (Chapter 8 of Textbook B) Lecture 14: Topic Models, Nonnegative Matrix Factorization, Hidden Markov Models and Graphical Models (Chapter 9 of Textbook B)
## ContactInstructor: Jinwoo Shin (jinwoos@kaist.ac.kr) |