tensorflow/ranking

Health v2 · maintenance only

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2773 stars · 477 forks observed · 2026-08-28

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

TensorFlow Ranking is a Python library for building Learning-to-Rank (LTR) models on top of TensorFlow. It provides pointwise, pairwise, and listwise loss functions, ranking metrics like MRR and NDCG, groupwise scoring functions, LambdaLoss, and unbiased learning-to-rank techniques.

Use cases

• train a learning-to-rank model for search results
• optimize NDCG directly with LambdaLoss
• evaluate ranking models with MRR and NDCG metrics
• build unbiased ranking models from biased click feedback
• score document lists with groupwise scoring functions
• train a ranking model for a recommender system

When to choose

• you need deep learning based ranking models in TensorFlow
• you want state-of-the-art LTR losses and metrics out of the box
• you are doing academic or industrial research on learning-to-rank

When to avoid

• your project uses PyTorch or JAX instead of TensorFlow
• you need simple classical LTR algorithms like LambdaMART without deep learning
• you need a actively evolving library with frequent releases

Facets

library · maturity maintenance

machine-learning deep-learning search-engine machine-learning python learning-to-rank tensorflow ranking-metrics lambdaloss ndcg mrr unbiased-ltr search information-retrieval recommender-systems linux gpu

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