[](https://pypi.org/project/alpha-automl/0.2.0/)
[](https://opensource.org/licenses/Apache-2.0)
[](https://github.com/VIDA-NYU/alpha-automl/actions/workflows/build.yml)
[](https://alpha-automl.readthedocs.io/en/latest/?badge=latest)
<img src="https://github.com/VIDA-NYU/alpha-automl/raw/devel/Alpha-AutoML_logo.png" width=30%>
Alpha-AutoML is an AutoML system that automatically searches for models and derives end-to-end pipelines that read,
pre-process the data, and train the model. Alpha-AutoML leverages recent advances in deep reinforcement learning and is
able to adapt to different application domains and problems through incremental learning.
Alpha-AutoML provides data scientists and data engineers the flexibility to address complex problems by leveraging the
Python ecosystem, including open-source libraries and tools, support for collaboration, and infrastructure that enables
transparency and reproducibility.
This repository is part of New York University's implementation of the
[Data Driven Discovery project (D3M)](https://datadrivendiscovery.org/).
## Documentation
Documentation is available [here.](https://alpha-automl.readthedocs.io/)
## Installation
This package works with Python 3.6+ in Linux, Mac, and Windows.
You can install the latest stable version of this library from [PyPI](https://pypi.org/project/alpha-automl/):
```
pip install alpha-automl
```
To install the latest development version:
```
pip install git+https://github.com/VIDA-NYU/alpha-automl@devel
```
## Trying it using Docker
We provide pre-built docker images with Jupyter and Alpha-AutoML pre-installed that you can use to quickly test Alpha-AutoML.
To test it, you can run the following command in your machine, and open Jupyter Notebook on your browser:
```
docker run -p 8888:8888 ghcr.io/vida-nyu/alpha-automl
```
Using this command, Jupyter Notebook will auto-generate a security token. The correct URL to access the Jupyter will be printed in the console output and will look like: `http://127.0.0.1:8888/?token=70ace7fa017c35ba0134dc7931add12bf55a69d4d4e6e54f`.
Alternatively, if you want to provide a custom security token, you can run:
```
docker run -p 8888:8888 -e JUPYTER_TOKEN="<my-token>" ghcr.io/vida-nyu/alpha-automl
```
If you are running the Jupyter Notebook in a secure environment, the authentication can be disabled as follows:
```
docker run -p 8888:8888 ghcr.io/vida-nyu/alpha-automl --NotebookApp.token=''
```
## Building a Docker image from scratch
If you need to build an image from sources, you can use our [Dockerfile](https://github.com/VIDA-NYU/alpha-automl/blob/devel/Dockerfile). You can use a docker-build argument to select the packages that will be installed in the image (e.g., `full`, `timeseries`, `nlp`, etc) as follows:
```
docker build -t alpha-automl --build-arg BUILD_OPTION=full .
```
Or simply a base version using (this will use less disk space but will not provide support for some tasks such as NLP and timeseries):
```
docker build -t alpha-automl:latest --target alpha-automl .
```
You can also build an image to use with JupyterHub as follows:
```
docker build -t alpha-automl:latest-jupyterhub --target alpha-automl-jupyterhub .
```
See also the documentation on how to setup Alpha-AutoML + JupyterHub on [Kubernetes](https://github.com/VIDA-NYU/alpha-automl/tree/devel/kubernetes).
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