JuliaML/LossFunctions.jl
Julia package of loss functions for machine learning.
This package helps machine learning developers efficiently evaluate how well their models are performing. You input the true target values and your model's predicted outputs, and it calculates a score that quantifies the prediction error. It's used by machine learning engineers, data scientists, and researchers building and refining predictive models.
150 stars.
Use this if you are a Julia machine learning developer who needs a robust collection of pre-implemented loss functions to measure model error.
Not ideal if you are looking for a high-level machine learning framework or do not work with the Julia programming language.
Stars
150
Forks
34
Language
Julia
License
—
Category
Last pushed
Mar 09, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/JuliaML/LossFunctions.jl"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
CliMA/Oceananigans.jl
🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs
JuliaLang/julia
The Julia Programming Language
WassimTenachi/PhySO
Physical Symbolic Optimization
EnzymeAD/Enzyme.jl
Julia bindings for the Enzyme automatic differentiator
astroautomata/SymbolicRegression.jl
Distributed High-Performance Symbolic Regression in Julia