Metadata-Version: 2.1
Name: deepmatch
Version: 0.1.2
Summary: Deep matching model library for recommendations, advertising. It's easy to train models and to **export representation vectors** for user and item which can be used for **ANN search**.
Home-page: https://github.com/shenweichen/deepmatch
Author: Weichen Shen
Author-email: wcshen1994@163.com
License: Apache-2.0
Download-URL: https://github.com/shenweichen/deepmatch/tags
Keywords: match,matching,recommendationdeep learning,tensorflow,tensor,keras
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*
Description-Content-Type: text/markdown
Provides-Extra: cpu
Provides-Extra: gpu
Requires-Dist: h5py
Requires-Dist: requests
Requires-Dist: deepctr (==0.7.4)
Provides-Extra: cpu
Requires-Dist: tensorflow (!=1.7.*,!=1.8.*,>=1.4.0); extra == 'cpu'
Provides-Extra: gpu
Requires-Dist: tensorflow-gpu (!=1.7.*,!=1.8.*,>=1.4.0); extra == 'gpu'

# DeepMatch

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)](https://github.com/shenweichen/deepmatch/issues)
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DeepMatch is a deep matching model library for recommendations & advertising. It's easy to **train models** and to **export representation vectors** for user and item which can be used for **ANN search**.You can use any complex model with `model.fit()`and `model.predict()` .

Let's [**Get Started!**](https://deepmatch.readthedocs.io/en/latest/Quick-Start.html) or [**Run examples**](./examples/colab_MovieLen1M_YoutubeDNN.ipynb) !



## Models List

|                 Model                  | Paper                                                                                                                                                           |
| :------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|  FM  | [ICDM 2010][Factorization Machines](https://www.researchgate.net/publication/220766482_Factorization_Machines) |
| DSSM | [CIKM 2013][Deep Structured Semantic Models for Web Search using Clickthrough Data](https://www.microsoft.com/en-us/research/publication/learning-deep-structured-semantic-models-for-web-search-using-clickthrough-data/)    |
| YoutubeDNN     | [RecSys 2016][Deep Neural Networks for YouTube Recommendations](https://www.researchgate.net/publication/307573656_Deep_Neural_Networks_for_YouTube_Recommendations)            |
| NCF  | [WWW 2017][Neural Collaborative Filtering](https://arxiv.org/abs/1708.05031)       |
| MIND  | [CIKM 2019][Multi-interest network with dynamic routing for recommendation at Tmall](https://arxiv.org/pdf/1904.08030)  |

## Contributors([welcome to join us!](./CONTRIBUTING.md))

<table border="0">
  <tbody>
    <tr align="center" >
      <td>
        ​ <a href="https://github.com/shenweichen"><img width="70" height="70" src="https://github.com/shenweichen.png?s=40" alt="pic"></a><br>
        ​ <a href="https://github.com/shenweichen">Shen Weichen</a> ​
        <p>
        Alibaba Group  </p>​
      </td>
      <td>
         <a href="https://github.com/wangzhegeek"><img width="70" height="70" src="https://github.com/wangzhegeek.png?s=40" alt="pic"></a><br>
         <a href="https://github.com/wangzhegeek">Wang Zhe</a> ​
        <p>Jingdong Group  </p>​
      </td>
      <td>
        ​ <a href="https://github.com/LeoCai"><img width="70" height="70" src="https://github.com/LeoCai.png?s=40" alt="pic"></a><br>
         <a href="https://github.com/LeoCai">LeoCai</a>
         <p>  ByteDance   </p>​
      </td>
      <td>
        ​ <a href="https://github.com/yangjieyu"><img width="70" height="70" src="https://github.com/yangjieyu.png?s=40" alt="pic"></a><br>
        ​ <a href="https://github.com/yangjieyu">Yang Jieyu</a>
        <p> Zhejiang University   </p>​
      </td>
    </tr>
  </tbody>
</table>

## DisscussionGroup  

Please follow our wechat to join group:  
- 公众号：**浅梦的学习笔记**  
- wechat ID: **deepctrbot**

  ![wechat](./docs/pics/weichennote.png)


