johan010 / adanet

Fast and flexible AutoML with learning guarantees.

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AdaNet

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AdaNet is a lightweight and scalable TensorFlow AutoML framework for training and deploying adaptive neural networks using the AdaNet algorithm [Cortes et al. ICML 2017]. AdaNet combines several learned subnetworks in order to mitigate the complexity inherent in designing effective neural networks.

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This is not an official Google product.

Getting Started

To get you started:

Requirements

adanet depends on bug fixes and enhancements not present in TensorFlow releases prior to 1.7. You must install or upgrade your TensorFlow package to at least 1.7:

$ pip install "tensorflow>=1.7.0"

Installing from source

To install from source first you'll need to install bazel following their installation instructions.

Next clone adanet and cd into its root directory:

$ git clone https://github.com/tensorflow/adanet && cd adanet

From the adanet root directory run the tests:

$ cd adanet
$ bazel test -c opt //...

Once you have verified that everything works well, install adanet as a pip package .

You are now ready to experiment with adanet.

import adanet

License

AdaNet is released under the Apache License 2.0.

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Fast and flexible AutoML with learning guarantees.

License:Apache License 2.0


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