All office hours are now on Zoom. See Piazza for links.
Prof. Ryan Adams (OH: Mon/Wed 1-3pm)
TA: Haochen Li (OH: Mon 7-9pm)
TA: Sulin Liu (OH: Thu 7-9pm)
TA: Geoffrey Roeder (OH: Wed 4:30-6:30pm)
TA: Ari Seff (OH: Thu 5-7pm)
TA: Alexander Strzalkowski (OH: Tue 5-7pm)
TA: Fangyin Wei (OH: Fri 4-6pm)
Lab TA: Michael Li (OH: Sun 2-4pm)
Lab TA: Alan Chung (OH: Sat 11am-1pm)
Lab TA: Kenny Peng (OH: Mon 5-7pm, COS 401)
Lecture: Course Introduction [slides]
Assignment 1 Out
Lecture: Vectors and Matrices
Precept: Solving linear systems [slides] [COS_302_Precept_1.ipynb]
Lecture: Solving linear systems, continued [Colab Notebook on Gauss-Jordan]
Assignment 2 Out
Lecture: Groups and vector spaces [Colab Notebook for Color Subspaces]
Assignment 1 Due
Precept: Basis concepts [slides]
Lecture: Basis concepts, continued
Assignment 3 Out
Lecture: Norms and inner products
Assignment 2 Due
Precept: Orthogonality [slides]
Lecture: Projections, continued
Assignment 4 Out
Lecture: Eigenvectors and eigenvalues [Colab notebook demo]
Assignment 3 Due
Precept: Eigendecomposition and Cholesky factors
[slides, Python notebook]
Lecture: Singular value decomposition
Assignment 5 Out
Lecture: Singular value decomposition, continued
Assignment 4 Due
Precept: Other matrix decompositions
[slides]
Lecture: Catchup and Review [ video 1 on HW4 P2, video 2 on HW4 P5 ]
IN-CLASS MIDTERM EXAM
No precept
Lecture: Differentiation
Assignment 6 Out
Lecture: Multivariate differentiation
Assignment 5 Due
Precept: Multivariate differentiation, continued [slides, video]
Lecture: Random variables
Assignment 7 Out
Lecture: Random variables
Assignment 6 Due
Precept: Sampling from distributions [video, annotated slides, Colab notebook]
Lecture: Independent and dependent random variables
Assignment 8 Out
Lecture: Aggregating random variables
Assignment 7 Due
Precept: Transforming random variables [slides, video]
Lecture: Multivariate Gaussian distributions
Assignment 9 Out
Lecture: Monte Carlo estimation
Assignment 8 Due
Precept: Monte Carlo estimation, continued [video]
Lecture: Information theory
Assignment 10 Out
Lecture: Optimization basics
Assignment 9 Due
Precept: Constrained optimization
Lecture: Convex optimization
Assignment 11 Out
Precept: Questions and Answers