An General Automated Machine Learning Framework
Project description
Hypernets
Hypernets: A General Automated Machine Learning Framework
Hypernets is a general AutoML framework, based on which it can implement automatic optimization tools for various machine learning frameworks and libraries, including deep learning frameworks such as tensorflow, keras, pytorch, and machine learning libraries like sklearn, lightgbm, xgboost, etc. We introduced an abstract search space representation, taking into account the requirements of hyperparameter optimization and neural architecture search(NAS), making Hypernets a general framework that can adapt to various automated machine learning needs.
Overview
Conceptual Model
Illustration of the Search Space
Installation
pip install hypernets
Verify installation:
python -c "from examples import smoke_testing;"
Hypernets related projects
- HyperGBM: A full pipeline AutoML tool integrated various GBM models.
- HyperDT/DeepTables: An AutoDL tool for tabular data.
- HyperKeras: An AutoDL tool for Neural Architecture Search and Hyperparameter Optimization on Tensorflow and Keras.
- Cooka: Lightweight interactive AutoML system.
- Hypernets: A general automated machine learning framework.
Neural Architecture Search
DataCanvas
Hypernets is an open source project created by DataCanvas.
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