# easyrec **Repository Path**: mirrors/easyrec ## Basic Information - **Project Name**: easyrec - **Description**: 阿里云EasyRec是一款开源的推荐算法框架，该框架包括了数据处理、特征提取、模型训练和推荐服务四个环节，其中包含DeepFM、DIN、MultiTower及DSSM等经典推荐排序 - **Primary Language**: Python - **License**: Apache-2.0 - **Default Branch**: master - **Homepage**: https://www.oschina.net/p/easyrec - **GVP Project**: No ## Statistics - **Stars**: 36 - **Forks**: 11 - **Created**: 2023-06-06 - **Last Updated**: 2025-06-08 ## Categories & Tags **Categories**: ai **Tags**: None ## README # EasyRec Introduction 🎉 See our ongoing recommendation framework **[TorchEasyRec](https://github.com/alibaba/TorchEasyRec) !** 🎉 This evolution of EasyRec is built on **PyTorch**, featuring **GPU acceleration** and **hybrid parallelism** for enhanced performance.   ## What is EasyRec? ![intro.png](docs/images/intro.png) ### EasyRec is an easy-to-use framework for Recommendation EasyRec implements state of the art deep learning models used in common recommendation 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).   ## Get Started Running Platform: - [Local examples](examples/readme.md) - [MaxCompute](docs/source/quick_start/mc_tutorial.md) - [EMR-DataScience](docs/source/quick_start/emr_tutorial.md) - [PAI-DSW (DEMO)](https://dsw-dev.data.aliyun.com/#/?fileUrl=http://easyrec.oss-cn-beijing.aliyuncs.com/dsw/easy_rec_demo.ipynb&fileName=EasyRec_DeepFM.ipynb)   ## Why EasyRec? ### Run everywhere - Local / [MaxCompute](https://help.aliyun.com/product/27797.html) / [EMR-DataScience](https://help.aliyun.com/document_detail/170836.html) / [DLC](https://www.alibabacloud.com/help/zh/doc-detail/165137.htm) - TF1.12-1.15 / TF2.x / PAI-TF ### Diversified input data - [MaxCompute Table](https://help.aliyun.com/document_detail/27819.html) - HDFS files / Hive Table - [OSS files](https://help.aliyun.com/product/31815.html) - CSV files / Parquet files - Datahub / Kafka Streams ### Simple to config - Flexible feature config and simple model config - [Build models by combining some components](docs/source/component/backbone.md) - Efficient and robust feature generation\[used in taobao\] - Nice web interface in development ### It is smart - EarlyStop / Best Checkpoint Saver - [Hyper Parameter Search](docs/source/automl/pai_nni_hpo.md) / [AutoFeatureCross](docs/source/automl/auto_cross_emr.md) / [Knowledge Distillation](docs/source/kd.md) / [Features Selection](docs/source/feature/feature.rst#id4) - In development: NAS ### Large scale and easy deployment - Support large scale embedding and [online learning](docs/source/online_train.md) - Many parallel strategies: ParameterServer, Mirrored, MultiWorker - Easy deployment to [EAS](https://help.aliyun.com/document_detail/113696.html): automatic scaling, easy monitoring - Consistency guarantee: train and serving ### A variety of models - [DSSM](docs/source/models/dssm.md) / [MIND](docs/source/models/mind.md) / [DropoutNet](docs/source/models/dropoutnet.md) / [CoMetricLearningI2I](docs/source/models/co_metric_learning_i2i.md) / [PDN](docs/source/models/pdn.md) - [W&D](docs/source/models/wide_and_deep.md) / [DeepFM](docs/source/models/deepfm.md) / [MultiTower](docs/source/models/multi_tower.md) / [DCN](docs/source/models/dcn.md) / [FiBiNet](docs/source/models/fibinet.md) / [MaskNet](docs/source/models/masknet.md) / [PPNet](docs/source/models/ppnet.md) / [CDN](docs/source/models/cdn.md) - [DIN](docs/source/models/din.md) / [BST](docs/source/models/bst.md) / [CL4SRec](docs/source/models/cl4srec.md) - [MMoE](docs/source/models/mmoe.md) / [ESMM](docs/source/models/esmm.md) / [DBMTL](docs/source/models/dbmtl.md) / [AITM](docs/source/models/aitm.md) / [PLE](docs/source/models/ple.md) - [HighwayNetwork](docs/source/models/highway.md) / [CMBF](docs/source/models/cmbf.md) / [UNITER](docs/source/models/uniter.md) - More models in development ### Easy to customize - Support [component-based development](docs/source/component/backbone.md) - Easy to implement [customized models](docs/source/models/user_define.md) and [components](docs/source/component/backbone.md#id12) - Not need to care about data pipelines ### Fast vector retrieve - Run [knn algorithm](docs/source/vector_retrieve.md) of vectors in distribute environment   ## Document - [Home](https://easyrec.readthedocs.io/en/latest/) - [FAQ](https://easyrec.readthedocs.io/en/latest/faq.html) - [EasyRec Framework](https://easyrec.oss-cn-beijing.aliyuncs.com/docs/EasyRec.pptx)(PPT)   ## 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](docs/source/develop.md) document for more details.   ## Cite If EasyRec is useful for your research, please cite: ``` @article{Cheng2022EasyRecAE, title={EasyRec: An easy-to-use, extendable and efficient framework for building industrial recommendation systems}, author={Mengli Cheng and Yue Gao and Guoqiang Liu and Hongsheng Jin and Xiaowen Zhang}, journal={ArXiv}, year={2022}, volume={abs/2209.12766} } ```   ## Contact ### Join Us - DingDing Group: 32260796. click [this url](https://page.dingtalk.com/wow/z/dingtalk/simple/ddhomedownload?action=joingroup&code=v1,k1,MwaiOIY1Tb2W+onmBBumO7sQsdDOYjBmv6FXC6wTGns=&_dt_no_comment=1&origin=11#/) or scan QrCode to join![dinggroup1.png](docs/images/qrcode/dinggroup1.png) - DingDing Group2: 37930014162, click [this url](https://page.dingtalk.com/wow/z/dingtalk/simple/ddhomedownload?action=joingroup&code=v1,k1,1ppFWEXXNPyxUClHh77gCmpfB+JcPhbFv6FXC6wTGns=&_dt_no_comment=1&origin=11#/) or scan QrCode to join![dinggroup2.png](docs/images/qrcode/dinggroup2.png) - Email Group: easy_rec@service.aliyun.com. ### 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.