.. For licensing see accompanying LICENSE file.
.. Copyright (C) 2023 Apple Inc. All Rights Reserved.

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Symphony
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**Reusable, explorable, and sharable data science components**

Symphony is a framework for composing interactive machine learning interfaces with task-specific, data-driven components that can be used across platforms such as computational notebooks and web dashboards. 

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      <source src="_static/Symphony.mp4" type="video/mp4">
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This code accompanies the following `research paper <https://machinelearning.apple.com/research/composing-interactive-interfaces>`__:

| **Symphony: Composing Interactive Interfaces for Machine Learning**
| Alex Bäuerle*, Ángel Alexander Cabrera*, Fred Hohman, Megan Maher,
| David Koski, Xavier Suau, Titus Barik, Dominik Moritz
| *ACM Conference on Human Factors in Computing Systems (CHI), 2022.*
| `Paper <https://arxiv.org/abs/2202.08946>`__, `Code <https://github.com/apple/ml-symphony/>`__, `Preview <https://www.youtube.com/watch?v=Wf-YRBsI-wA>`__, `Video <https://www.youtube.com/watch?v=0Q3wIh3AiPs>`__ \*Contributed equally

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Overview
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Check out the :doc:`start` page to install and use Symphony, or browse our :doc:`examples` to get an idea of the types of analyses Symphony enables.

If you want to create your own component, check out our :doc:`creation` page, or explore the Symphony code at our `GitHub repo <https://github.com/apple/ml-symphony>`__. 
    
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Table of Contents
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..  toctree::
    :maxdepth: 3

    start
    components
    creation
    state
    common
    examples
    contributing
    api
    genindex