EasyRec简介

🎉 See our ongoing recommendation framework TorchEasyRec ! 🎉 This evolution of EasyRec is built on PyTorch, featuring GPU acceleration and hybrid parallelism for enhanced performance.

What is EasyRec?

EasyRec is an easy-to-use framework for Recommendation

EasyRec implements state of the art machine 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).

EasyRec视频介绍

Why EasyRec?

Run everywhere

• MaxCompute / DataScience / DLC / Local

• TF1.12-1.15 / TF2.x / PAI-TF

Diversified input data

• MaxCompute Table

• HDFS files

• OSS files

• Kafka Streams

• Local CSV

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

• EarlyStop / Best Checkpoint Saver

• Hyper Parameter Search / AutoFeatureCross

• In development: NAS, Knowledge Distillation, MultiModal

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

• DSSM / MIND / DropoutNet / CoMetricLearningI2I / PDN

• W&D / DeepFM / MultiTower / DCN / DIN / BST

• MMoE / ESMM / DBMTL / PLE

• CMBF / UNITER

• More models in development

Easy to customize

• Easy to implement customized models

• Not need to care about data pipelines

Fast vector retrieve

• Run knn algorithm of vectors in distribute environment

Contact

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

• DingDing Group: 37930014162, click this url or scan QrCode to join