Tuesday, July 12 & Thursday, July 14
9:30am–12:30pm Pacific Time
This course, suitable for people with no knowledge of machine learning, will walk you through the core concepts of deep neural networks. We will use PyTorch, a framework extremely popular in academic research.
Instructor: Marie-Hélène Burle (SFU)
Prerequisites: Working knowledge of Python or attendance at the Basics of Python course.
Zoom Day 1 – 9:30am–9:40am Pacific
On your own
Zoom Day 1 – 11:00am–12:30pm Pacific
Overarching concept of deep learning
Which framework to choose?
PyTorch API & libraries
(Optional) Local installation
Higher-level frameworks built on top of PyTorch
Zoom Day 2 – 9:30am–12:30pm Pacific
Creating a DataLoader from a classic audio dataset
Creating a DataLoader from a classic vision dataset
Building a neural network
Training a model
Saving/loading models and checkpointing
Machine learning on production clusters
A few notes on PyTorch distributed