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