Unverified Commit f0a6c3bf authored by Bharath Ramsundar's avatar Bharath Ramsundar Committed by GitHub
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Merge pull request #1057 from lilleswing/website-updates 

Website Updates
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website/about.html

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<!DOCTYPE html>

<html lang="en">

<head>

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    <title>DeepChem</title>

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<body id="home">



<header>



    <div class="logo"><a href="./index.html" class="pull-left"><img src="./static/img/deepchem_logo.png" height="100"></a></a></div>



    <ul class="primary-nav">

      <li><a  href="./about.html">About</a></li>

      <li><a  href="http://deepchem.blogspot.com">Blog</a></li>

      <li><a  href="./docs/notebooks/index.html">Tutorials</a></li>

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      <li><a  href="./docs/deepchem.html">Docs</a></li>

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</header>



 <section class="content wrap">

     <div class="container">

    <h2>What is DeepChem?</h2>

    <p>

    DeepChem is a python library that provides a high quality open-source toolchain

    for deep-learning in drug discovery, materials science, quantum chemistry, and

    biology.

    </p>

    <h2>About Us</h2>

    <p>DeepChem is possible due to notable contributions from many people including Peter Eastman, Evan Feinberg, Joe Gomes, Karl Leswing, Vijay Pande, Aneesh Pappu, Bharath Ramsundar and Michael Wu (alphabetical ordering). DeepChem was originally created by <a class="reference external" href="https://rbharath.github.io">Bharath Ramsundar</a> with encouragement and guidance from Vijay Pande.</p>

    <p>DeepChem started as a Pande group project at Stanford, and is now developed by many academic and industrial collaborators. DeepChem actively encourages new academic and industrial groups to contribute!</p>

    <h2>Licensing and Commercial Uses</h2>

    <p>DeepChem is licensed under the MIT License. We actively support

    commercial users. Note that any novel molecular entities found through DeepChem

    belong entirely to the user and not to DeepChem developers.</p>

    <h2>Getting Started With DeepChem</h2>

    <p>New users should check out <a href="./index.html">installation</a> instructions.<br> <br>

    Two good tutorials to get started are <a href="./docs/notebooks/graph_convolutional_networks_for_tox21.html">Graph Convolutional Networks</a> and <a href="./docs/notebooks/Multitask_Networks_on_MUV.html">Multitask_Networks_on_MUV</a>. Follow along with the tutorials to see how to predict properties on molecules using neural networks. <br> <br>



    Afterwards you can go through other <a href="docs/notebooks/index.html">tutorials</a>, and look through our <a href="https://github.com/deepchem/deepchem/tree/master/examples">examples</a>. To apply DeepChem to a new problem, try starting from one of the existing examples or tutorials and modifying it step by step to work with your new use-case. If you have questions or comments you can raise them on our <a href="https://gitter.im/deepchem/Lobby">gitter</a>.

    </div>

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website/index.html

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