DeepRec-AI/DeepRec

Health v2 · maintenance only

Adoption not part of the score

1197 stars · 359 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

DeepRec is a high-performance deep learning framework for recommendation models, built on TensorFlow 1.15 with Intel and NVIDIA TensorFlow enhancements. It supports super-large-scale distributed training and serving of sparse embedding-based models, incubated under the LF AI & Data Foundation.

Use cases

• train recommendation models with trillion-scale sparse parameters
• run distributed parameter-server training for CTR prediction models
• serve large embedding-based models with low latency
• optimize recommendation training on CPU and GPU clusters
• handle huge sparse id features for search and advertising models
• deploy online learning pipelines for ads ranking

When to avoid

• you need modern TensorFlow 2.x or PyTorch ecosystems
• your models are small or dense (CV, NLP) without huge embedding tables
• you want a lightweight framework with a small dependency footprint

Facets

framework · maturity active

deep-learning machine-learning llm-training machine-learning deep-learning microservices python cpp recommendation-systems tensorflow distributed-training embedding parameter-server model-serving sparse-embedding recommendation-engine advertising search linux gpu docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="DeepRec-AI/DeepRec")