I am excited to announce the release of FastAI.jl, a fastai-like library for deep learning in Julia. Features include high-level training loops with hyperparameter scheduling and callbacks, a data block API, learning rate finder, dataset loading, efficient data augmentation, visualizations, logging, effcicient data loading and many more. You can get started without installing Julia using this Google Colab template and following the documentation.
See the release post on the Julia Discourse for more information. We’ll also be hosting a Q&A session 02.08., 10PM UTC (03.08., 12AM CEST | 8AM AEST). Jeremy will be there, too. Meeting link will follow soon.
We’re glad to get feedback from the Python fastai community! You can open issues on the GitHub repository, comment on this thread or say hi on the Julia Zulip channel #ml-ecosystem-coodination where the devs are active with any feedback, comments, or problems you might have.
