/UT-Dallas-CS-6301-CNNs

UT Dallas CS 6301 Convolutional Neural Networks

This is the home page for a 1 semester graduate special topics course on convolutional neural networks in the Computer Science Department at UT Dallas that covers:

  • Math: linear algebra, calculus, probability and algorithms
  • Networks: design, training and implementation
  • Applications: vision, speech, language, games (to be added) and art (to be added)

While the title of the course is convolutional neural networks, the course covers many parts of deep learning including convolutional neural networks, recurrent neural networks, attention and variants.

The slides were created for the 1st time that the class was taught in the Fall 2018 semester. These are gradually being revised for the 2nd time that the class is being taught in the Spring 2019 semester. Expect continual updates throughout the Spring semester for both slides in the Lectures directory and complementary code in the Code directory.

Introduction

Introduction

Math

Linear algebra
Calculus
Probability
Algorithms

Networks

Design
Training
Implementation

Applications

Vision
Speech
Language
Games
Art

Summary

Summary