Deep Learning IE 534, Fall 2018
Instructor: Justin Sirignano 
What is Deep Learning?
Deep learning has revolutionized image recognition, speech recognition, and natural language processing. There's also growing interest in applying deep learning to engineering, robotics, biotechnology, medicine, and finance.
At a high level, deep neural networks are stacks of nonlinear operations, typically with millions of parameters. This produces a highly flexible and powerful model which has proved effective in many applications. The design of network architectures and optimization methods have been the focus of intense research. Course overview
Topics include convolution neural networks, recurrent neural networks, and deep reinforcement learning. Homeworks on image classification, video recognition, and deep reinforcement learning. Training of deep learning models using TensorFlow and PyTorch. A large amount of GPU resources are provided to the class. See Syllabus for more details. Mathematical analysis of neural networks, reinforcement learning, and stochastic gradient descent algorithms will also be covered in lectures. (However, there will be no proofs in homeworks and the midterm.)
IE 534 Deep Learning will be crosslisted with CS 547.
This course is part of the Deep Learning sequence:
A large amount of GPU resources are provided to the class. Graphics processing units (GPUs) can massively parallelize the training of deep learning models. The course has a 50,000 GPU hour allocation. This is a unique opportunity for students to develop sophisticated deep learning models at large scales. Code
Extensive TensorFlow and PyTorch code is provided to students. This code is distributed to UIUC students who are enrolled in the course. Homeworks
In HW6, a deep learning model is trained to predict the action occurring in a video solely using the raw pixels in the sequence of frames. The five most likely actions according to the deep learning model are reported (selected from a total of 400 possible actions).
In HW9, a deep learning model learns to play the Atari video game using only the raw pixels in the sequence of frames (as a human would learn).
