Neuraxio/Neuraxle
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
Neuraxle helps machine learning engineers and data scientists build and deploy robust machine learning models more efficiently. It allows you to construct complex data processing and model training pipelines from reusable components, making it easier to manage and scale your ML projects. You input raw data and a collection of ML models and transformations, and it outputs a highly optimized, production-ready machine learning pipeline.
614 stars. Available on PyPI.
Use this if you are a machine learning engineer or data scientist who needs to build, organize, and fine-tune complex machine learning pipelines for production, especially when working with various ML libraries.
Not ideal if you are a data analyst or business user looking for a low-code or no-code solution for quick data analysis without deep involvement in ML model development.
Stars
614
Forks
63
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 20, 2026
Commits (30d)
0
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