BME69500DL: Deep Learning
Spring 2021
Purdue University
School of Electrical and Computer Engineering
Week 1; Lecture 1 (Kak and Bouman) Introduction to Class
Week 1; Lecture 2 (Bouman) Machine Learning; Single Layer Neural Networks
Week 2; Lecture 1 (Kak) Intro to Python and Object Oriented Programming
Week 2; Lecture 2 (Bouman) The Loss Function, and Gradient Descent
Week 3; Lecture 1 (Kak)
Week 3; Lecture 2 (Bouman) Tensors and Tensor Operations
Week 4; Lecture 1 (Kak) Autograde and Computational Graphs
Week 4; Lecture 2 (Bouman) Gradients for Single Layer Networks
Week 5; Lecture 1 Cancelled due to snow
Week 5; Lecture 2 (Kak) Autograd (Bouman) Deep Networks
Week 6; Lecture 1 (Kak) Pytorch and Convolutional Neural Networks
Week 6; Lecture 2 (Bouman) Optimization of Deep Networks
Week 7; Lecture 1 (Kak/Bouman) Convolution Neural Networks
Week 7; Lecture 2 (Kak/Bouman) Multi-Channel CNNs
Week 8; Lecture 1 (Kak) Skip Connections and Batch Normalization
Week 8; Lecture 2 (Bouman) Exam
Week 9; Lecture 1 (Kak) Object Detection and Localization
Week 9; Lecture 2 Reading Day
Week 11; Lecture 1 (Kak) Object Detection and Localization
Week 11; Lecture 2 (Bouman) Probability and Estimation
Week 12; Lecture 1 (Kak) Multiple Instance Object Detection
Week 12; Lecture 2 (Kak/Bouman) Multiple Instance Object Detection/Training and Generalization
Week 13; Lecture 1 (Kak) Encoder-Decoder Architectures
Week 13; Lecture 2 (Bouman) Stochastic Gradient Descent
Week 14; Lecture 2 (Kak/Bouman) Recurrent Neural Networks/Widely used Techniques
Week 15; Lecture 1 (Kak) Word Embedding and Sequence-to-Sequence Learning
Week 16; Lecture 1 (Kak) GANs for Data Modeling
Week 16; Lecture 2 (Bouman) Adversarial Learning