Course Description
This course provides a comprehensive introduction to deep neural networks. Major topics include multilayer perceptrons, convolutional neural networks, recurrent neural networks, practical aspects of training deep neural networks and generative probabilistic modeling with deep neural networks. Students will learn basic concepts of deep learning as well as hands on experience to solve real-life problems. This course requires strong background in linear algebra, probability and statistics and machine learning. Python will be used for all the assignments.
Optional Textbook
Deep Learning Frameworks
Tentative Schedule
| Date | Lecture | Misc |
|---|---|---|
| Introduction | ||
| Wed Aug 29 | Welcome | |
| Mon Sep 03 | No Class (holiday) | |
| Wed Sep 05 | Machine Learning Review | Homework 1 Out |
| Mon Sep 10 | No Class (instructor out-of-office) | |
| Wed Sep 12 | No Class (instructor out-of-office) | Homework 1 Due |
| Deep Networks | ||
| Mon Sep 17 | Feed Forward Networks: Introduction | |
| Wed Sep 19 | Feed Forward Networks: Learning | Homework 2 Out |
| Mon Sep 24 | Backpropagation | |
| Wed Sep 26 | Automatic Differentiation | Homework 2 Due |
| Mon Oct 01 | Optimization | Homework 3 Out |
| Supervised Learning | ||
| Wed Oct 03 | Convolutional Neural Networks | |
| Mon Oct 08 | Alternative Convolutional Layers | Homework 3 Due, Programming Assignment 1 Out |
| Wed Oct 10 | Modeling Sequences with Neural Networks | |
| Mon Oct 15 | Modeling Long-Term Dependencies | |
| Wed Oct 17 | Practical Tricks for Training | Programming Assignment 1 Due, Homework 4 Out |
| Mon Oct 22 | No-class (instructor out-of-office) | |
| Wed Oct 24 | No-class (instructor out-of-office) | Homework 4 Due, Programming Assignment 2 Out |
| Mon Oct 29 | Supervised Learning Applications - I | |
| Wed Oct 31 | Supervised Learning Applications - II | |
| Unsupervised Learning | ||
| Mon Nov 05 | Autoencoders | Programming Assignment 2 Due |
| Wed Nov 07 | Deep Generative Models - I | Programming Assignment 3 Out |
| Mon Nov 12 | Deep Generative Models - II | |
| Wed Nov 14 | Deep Generative Models - III | |
| Mon Nov 19 | Applications of Deep Generative Models | Programming Assignment 3 Due |
| Assorted Topics | ||
| Wed Nov 21 | Max-Margin Learning and Siamese Networks | Programming Assignment 4 Out |
| Mon Nov 26 | Deep Reinforcement Learning - I | |
| Wed Nov 28 | Deep Reinforcement Learning - II | Homework 5 Out |
| Mon Dec 03 | Playing Go with Deep Neural Networks | |
| Wed Dec 05 | Course Review | Programming Assignment 4 Due |
| Tue Dec 11 | Final Exam (12:45pm-2:45pm) |