Jonathan Doucette
A PhD Candidate at the University of British Columbia, Jonathan Doucette studies MRI Physics and focuses on researching brain tissue microstructure through numerical simulation and Bayesian machine learning.
Session
07-26
10:00
30min
Ignite.jl: A brighter way to train neural networks
Jonathan Doucette
We introduce Ignite.jl, a package that streamlines neural network training and validation by replacing traditional for/while loops and callback functions with a powerful and flexible event-based pipeline. The key feature of Ignite.jl is the separation of the training step from the training loop, which gives users the flexibility to easily incorporate events such as artifact saving, metric logging, and model validation into their training pipelines without having to modify existing code.
JuliaCon
Online talks and posters