Schedule



Week Date Lecture (Mon) Date Lecture (Wed) Lab Advanced Section (Wed) Assignment (release and due)
1 28-Jan Lecture 1: Intro + Review of 109A Preview of 109B 30-Jan Lecture 2: Smoothing and Additive 1/3 Lab 1: Setting up enviroment
2 4-Feb Lecture 3: Smoothing and Additive 2/3 6-Feb Lecture 4: Smoothing and GAM 3/3 Lab 2: Smoothing/GAM HW1 (2/3)
3 11-Feb Lecture 5: Feed Forward + Reg + Review from NN fall 13-Feb Lecture 6: Optimization of NN (Solvers) Lab 3: Optimization Advanced Section 1: Optimization/Dropout HW2 (2/10)
4 18-Feb Holiday 20-Feb Lecture 7: AWS scalable systems SQL Lab 4: Setting UP AWS Advanced Section 2: Optimal Transport
5 25-Feb Lecture 8: CNNs-1 27-Feb Lecture 9: CNNs-2 Lab 5: CNNs Advanced Section 3: CNNs and Object Detection HW3 (2/24)
6 4-Mar Lecture 10: RNN 1 6-Mar Lecture 11: RNN 2 Lab 6: RNNS Advanced Section 4: RNNs HW4 (3/3)
7 11-Mar Lecture 12: Unsupervised learning/clustering 1 13-Mar Lecture 13: Unsupervised learning/clustering 2 Lab 7: Clusterig Advanced Section 5: Neural Style Transfer HW5 (3/10)
8 25-Mar Lecture 14: Reinforcement Learning 27-Mar Lecture 15: Bayesian 1/3 Lab 8: Bayes 1 Advanced Section 6: Deep RL
9 1-Apr Lecture 16: Bayesian 2/3 3-Apr Lecture 17: Bayesian 3/3 Lab 9: Bayes 2 HW6 (3/30)
10 8-Apr Lecture 18: Generative Models Varational Autoenders 1 10-Apr Lecture 19: Generative Models Varational Autoenders 2 Lab 10: VAE Advanced Section 7: Variational Inference HW7 (4/7)
11 15-Apr Lecture 20: GANS 17-Apr Lecture 21: GANS 2 Lab 11: Adveserial Networks Advanced Section 8: GANS