Overview

Instructor: Jian Tao

Time: Friday, October 29, 2021 — 10:00AM-12:30PM CT

Location: Blocker 220 and online using Zoom

Prerequisites: Experience with Python

This PyTorch short course will introduce the basics of deep learning with PyTorch, an open source machine learning library developed primarily by Facebook's AI Research lab (FAIR). The basic concepts of deep learning methods will be covered, and PyTorch will be introduced with examples.

PyTorch is an open source machine learning library developed primarily by Facebook's AI Research lab (FAIR). It is based on the Torch library and used for applications such as computer vision and natural language processing. PyTorch provides tensor computing that could be accelerated with GPUs and TPUs and deep neural networks on a tape-based autodiff system. (wikipedia.org).

This short course will introduce the basics of deep learning and PyTorch with examples.

Agenda

This course focuses, among others, on the following topics:

• Brief introduction to machine learning (ML) and deep learning (DL) methods
• Open source ML/DL software packages
• Introduction to PyTorch
• Hands-on exercises

This short course will make use of the Jupyter interactive environment. A brief introduction to Jupyter will be covered if necessary.

Course Materials

• Introduction to Deep Learning with PyTorch (Fall 2021): PDF
• Deep Learning with PyTorch: https://pytorch.org/tutorials

Previous Course Materials

• Introduction to Deep Learning with PyTorch (Spring 2021): PDF