FluxML/Zygote.jl
21st century AD
This project helps machine learning engineers and researchers automatically calculate derivatives (gradients) of complex Julia code. You provide Julia functions or models, and it outputs the gradient of those functions, making it easier to optimize models and algorithms. It's designed for those building and training machine learning models or working on numerical optimization tasks in Julia.
1,559 stars. Actively maintained with 1 commit in the last 30 days.
Use this if you need to automatically compute the exact gradients of your Julia functions or machine learning models to enable efficient training and optimization.
Not ideal if your Julia code heavily relies on direct data mutation or complex exception handling within the functions you wish to differentiate.
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Mar 01, 2026
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