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A framework for large scale recommendation algorithms.

alibaba
alibaba
pushedAt 17 hours ago

alibaba/EasyRec

EasyRec Introduction

 

What is EasyRec?

intro.png

EasyRec is an easy to use framework for Recommendation

EasyRec implements state of the art deep learning models used in common recommedation tasks: candidate generation(matching), scoring(ranking), and multi-task learning. It improves the efficiency of generating high performance models by simple configuration and hyper parameter tuning(HPO).

 

Why EasyRec?

Run everywhere

Diversified input data

Simple to config

  • Flexible feature config and simple model config
  • Efficient and robust feature generation[used in taobao]
  • Nice web interface in development

It is smart

Large scale and easy deployment

  • Support large scale embedding, incremental saving
  • Many parallel strategies: ParameterServer, Mirrored, MultiWorker
  • Easy deployment to EAS: automatic scaling, easy monitoring
  • Consistency guarantee: train and serving

A variety of models

Easy to customize

 

Get Started

Running Platform:

 

Document

 

Contribute

Any contributions you make are greatly appreciated!

  • Please report bugs by submitting a GitHub issue.
  • Please submit contributions using pull requests.
  • please refer to the Development document for more details.

 

Contact

Join Us

  • DingDing Group: 32260796. (EasyRec usage general discussion.)

  • Email Group: [email protected].

Enterprise Service

  • If you need EasyRec enterprise service support, or purchase cloud product services, you can contact us by DingDing Group.

 

License

EasyRec is released under Apache License 2.0. Please note that third-party libraries may not have the same license as EasyRec.

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