ClimbsRocks/auto_ml
An automated machine learning library for training, tuning, and deploying models across scikit-learn, Keras, TensorFlow, XGBoost, and LightGBM.
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auto_ml automates the machine learning workflow including feature engineering, model selection, and hyperparameter optimization. It provides a simple Predictor API that handles data preprocessing, trains models using various backends, and can serialize trained models for production deployment. The library supports regression and classification tasks with built-in handling for categorical features, NLP text columns, and date fields.
Frequently asked
- What is ClimbsRocks/auto_ml?
- An automated machine learning library for training, tuning, and deploying models across scikit-learn, Keras, TensorFlow, XGBoost, and LightGBM.
- Is auto_ml open source?
- Yes — ClimbsRocks/auto_ml is open source, released under the MIT license.
- What language is auto_ml written in?
- ClimbsRocks/auto_ml is primarily written in Python.
- How popular is auto_ml?
- ClimbsRocks/auto_ml has 1.7k stars on GitHub.
- Where can I find auto_ml?
- ClimbsRocks/auto_ml is on GitHub at https://github.com/ClimbsRocks/auto_ml.