Best Practices on Recommendation Systems

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP

:star:Github Ranking:star: Github stars and forks ranking list. Github Top100 stars list of different languages. Automatically update daily. | Github仓库排名，每日自动更新

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

[Deprecated!] This is a data visualization project that converts historical data rankings into dynamic bar charts.

Check your ranking in GitHub! Don't forget to star ⭐ this repository.

Learning embeddings for classification, retrieval and ranking.

:star: Web frameworks for Go, most starred on GitHub

A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.

Learning to Rank in TensorFlow

Perplexity Scraper Track brand mentions, analyze rankings, and gain competitor intelligence from Perplexity. Get started in minutes.

Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Pre-Ranking, Ranking (CTR/CVR prediction), Post Ranking, Relevance, LLM, Reinforcement Learning and so on.

A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine

Analysis, Comparison, Trends, Rankings of Open Source Software, you can also get insight from more than 10 billion with natural language (powered by LLM). Follow us on Twitter: https://twitter.com/ossinsight

🕷️Github China/Global User Ranking, Global Warehouse Star Ranking (Github Action is automatically updated daily).

Multi-Task Deep Neural Networks for Natural Language Understanding

Large-scale linear classification, regression and ranking in Python

Discover your ranking on github :

Awesome Search - this is all about the (e-commerce, but not only) search and its awesomeness

ATP Tennis Rankings, Results, and Stats

A Collection of BM25 Algorithms in Python

DeText: A Deep Neural Text Understanding Framework for Ranking and Classification Tasks

An official implementation for "CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval"

allRank is a framework for training learning-to-rank neural models based on PyTorch.

Ranking Google Scholar search results based on the number of citations

[ACL2023] We introduce LLM-Blender, an innovative ensembling framework to attain consistently superior performance by leveraging the diverse strengths of multiple open-source LLMs. LLM-Blender cut the weaknesses through ranking and integrate the strengths through fusing generation to enhance the capability of LLMs.

Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & Collaborations.

Fast, differentiable sorting and ranking in PyTorch

JavaScript string ranking 0 for no match upto 1 for perfect... "String".score("str"); //=> 0.825