FluxML/FluxTraining.jl

A flexible neural net training library inspired by fast.ai

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Emerging

This package helps deep learning practitioners efficiently train their neural networks without repeatedly coding common functionalities. You provide your deep learning model, data, optimizer, and loss function, and it handles the complex training process, including tracking performance metrics and adjusting parameters. It's designed for machine learning engineers and researchers building and refining deep learning models.

122 stars. No commits in the last 6 months.

Use this if you are developing deep learning models in Julia and want to streamline your training process with pre-built, reusable components for tasks like metric tracking or hyperparameter scheduling.

Not ideal if you are not working with deep learning models or prefer to build every aspect of your training loop from scratch without abstraction.

deep-learning neural-networks machine-learning-engineering model-training ai-development
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 20 / 25

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Stars

122

Forks

25

Language

Julia

License

MIT

Last pushed

Dec 25, 2024

Commits (30d)

0

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