Date | Content | Resources |
---|---|---|
9/29 | Python, Probability Fundamentals | Section notes, Solutions, Python intro (notebook runnable), Python intro (html), Python slide deck | 10/6 | Linear Algebra and Linear Regression | Section notes, Solutions |
10/13 | Bias-Variance; Train-Test Split | Section notes, Solutions |
10/20 | Vector Calculus; MAP | Section notes, Solutions |
10/27 | Demonstrative Code, Convexity, Gradient Descent | Section notes, Solutions, |
11/2 | Midterm Review, Gradient Descent | Practice Midterm Questions, Practice Midterm Solutions, Section notes, Solutions |
11/10 | Kernels, PyTorch | Section notes, Solutions, PyTorch intro (notebook runnable), PyTorch intro (html) |
11/17 | Neural Networks | Section notes, PyTorch intro continued (notebook runnable), PyTorch intro continued (html) PyTorch neural networks (notebook runnable), PyTorch neural networks (html), Solutions |
12/1 | Convolutional Neural Networks, PCA and SVD | Section notes, Solutions |
12/8 | PCA and SVD | Section notes, Solutions |