wzhe06/SparrowRecSys resource

Health v2 · maintenance only

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2776 stars · 868 forks observed · 2026-08-28

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

SparrowRecSys is an open-source movie recommendation system implemented as a mixed Java/Scala/Python project combining TensorFlow, Spark, and Jetty Server. It implements classic deep learning recommendation models (Word2vec, DeepWalk, Wide&Deep, DeepFM, DIN, etc.) across offline training, nearline processing, and online serving, and serves as the companion project for a practical deep learning recommender systems course.

Use cases

• learn how to build a deep learning recommender system end to end
• implement Wide&Deep, DeepFM, or DIN recommendation models
• practice feature engineering and model training with MovieLens data
• study offline, nearline, and online recommendation architecture
• serve trained TensorFlow recommendation models behind a web server
• explore embedding techniques like Item2vec and DeepWalk for recommendations

When to choose

• you want a complete, runnable reference implementation of a deep learning recommender system
• you are studying recommendation system architecture from offline training to online serving
• you need working examples of classic CTR and recommendation models in TensorFlow

When to avoid

• you need a production-grade, scalable recommender platform for real traffic
• you want a pure Python or pure Java stack without mixed-language builds
• you need a maintained library with recent releases and active bug fixes

Facets

learning-resource · maturity stable

machine-learning deep-learning data-science etl streaming http-server machine-learning deep-learning education tutorials data-science python jvm cross-platform recommender-system tensorflow spark movielens embedding ctr-prediction movie-recommendation model-serving docker

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