Fast and Accurate ML in 3 Lines of Code
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A unified framework for machine learning with time series
Automated Machine Learning with scikit-learn
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Python library for portfolio optimization, factor model construction, and risk management built on scikit-learn
A modular active learning framework for Python
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
Transpile trained scikit-learn estimators and transformers to C, C#, Go, Java, JavaScript, PHP and Ruby.
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.
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.