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All Projects → DataCanvasIO → Hypernets

DataCanvasIO / Hypernets

Licence: Apache-2.0 license
A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

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python
139335 projects - #7 most used programming language
Jupyter Notebook
11667 projects

Labels

reinforcement-learningkerasmctshyperparameter-optimizationevolutionary-algorithmsnasmonte-carlo-tree-searchhyperparameter-tuningautomlneural-architecture-searchnasnetenasautodl

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Python Versions Downloads PyPI Version

We Are Hiring！

Dear folks, we are offering challenging opportunities located in Beijing for both professionals and students who are keen on AutoML/NAS. Come be a part of DataCanvas! Please send your CV to [email protected]. (Application deadline: TBD.)

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. As an abstraction computing layer, tabular toolbox, has successfully implemented in various tabular data types: pandas, dask, cudf, etc.

Overview

Conceptual Model

Illustration of the Search Space

Installation

Conda

Install Hypernets with conda from the channel conda-forge:

conda install -c conda-forge hypernets

Pip

Install Hypernets with different options:

  • Typical installation:
pip install hypernets
  • To run Hypernets in JupyterLab/Jupyter notebook, install with command:
pip install hypernets[notebook]
  • To run Hypernets in distributed Dask cluster, install with command:
pip install hypernets[dask]
  • To support dataset with simplified Chinese in feature generation,
    • Install jieba package before running Hypernets.
    • OR install Hypernets with command:
pip install hypernets[zhcn]
  • Install all above with one command:
pip install hypernets[all]

Verify installation:

python -m hypernets.examples.smoke_testing

Related Links

Hypernets related projects

  • Hypernets: A general automated machine learning (AutoML) framework.
  • HyperGBM: A full pipeline AutoML tool integrated various GBM models.
  • HyperDT/DeepTables: An AutoDL tool for tabular data.
  • HyperTS: A full pipeline AutoML&AutoDL tool for time series datasets.
  • HyperKeras: An AutoDL tool for Neural Architecture Search and Hyperparameter Optimization on Tensorflow and Keras.
  • HyperBoard: A visualization tool for Hypernets.
  • Cooka: Lightweight interactive AutoML system.

DataCanvas AutoML Toolkit

Documents

Neural Architecture Search

DataCanvas

Hypernets is an open source project created by DataCanvas.

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