Deep learning with fastai

Tuesday, July 6
9 am–5 pm Pacific Time

This course, suitable for people with no knowledge of machine learning, will walk you through the core concepts of neural networks and give you the tools necessary to build your own models to solve problems. We will use fastai—a deep learning library building on top of PyTorch—as it gives the option of high-level fast implementation without compromising with the lower level flexibility of PyTorch.

Instructor: Marie-Hélène Burle (WestGrid)

Prerequisites: Working knowledge of Python or attendance at the Basics of Python course.

Zoom   9–10 am Pacific Time
Opening session & Jupyter access
AI, machine learning, deep learning

On your own
What are neural networks & how do they learn?

Zoom   11:30–12:30 pm Pacific Time
Network architectures & practical considerations

On your own
Transfer learning
The Transformer
Which framework to choose?
PyTorch tensors

Zoom   2–5 pm Pacific Time
fastai
Jupyter tips
Implementation: upscaling images
Ethical considerations
Wrap-up & resources