UCSD ECE176: Introduction to Deep Learning & Applications (Winter)

Date	Lecture	Materials	Assignments
Jan 6	Introduction	Lecture 1
Jan 8	Nearest Neighbor and Linear Classifiers	Lecture 2	Assignment 1: KNN in Numpy
Jan 9	Jupyter Notebook Tutorial
Jan 13	Linear Classifier and Optimization	Lecture 3
Jan 15	MLP and Back-Propagation	Lecture 4	Assignment 2: Linear Classifiers in Numpy
Jan 16	Assignment 1 Due
Jan 20	Intro to CNN and Back-Propagation with CNN	Lecture 5
Jan 22	Different Elements in Training CNNs 1	Lecture 6	Assignment 3: Training MLP in Numpy (Toy Dataset)
Jan 23	Assignment 2 Due
Jan 27	Different Elements in Training CNNs 2	Lecture 7
Jan 29	Tutorial on Pytorch		Assignment 4: Training MLP in Numpy (CIFAR10)
Jan 30	Assignment 3 Due
Feb 3	Deep Network Architectures
Feb 5	Image Segmentation
Feb 6	Final Project Proposal Due
Feb 10	Visualizing Deep Networks
Feb 12	Object Detection 1: Box		Assignment 5
Feb 15	Assignment 4 Due
Feb 17	Object Detection 2: Mask and Pose
Feb 19	Recurrent Neural Networks
Feb 24	Video Understanding
Feb 26	Video Prediction		Assignment 6
Feb 27	Assignment 5 Due
Mar 3	Vision Transformer
Mar 5	Generative Adversarial Networks
Mar 10	Conditional Generative Adversarial Networks
Mar 12	Guest Lecture
Mar 15	Assignment 6 Due, Final Project Due