shawndr

shawndr's Stars

• beir-cellar/beir

  A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.

  Language:Python1.6k191

• qdrant/qdrant

  Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

  Language:Rust20.4k1.4k

• o19s/quepid

  Improve your Elasticsearch, OpenSearch, Solr, Vectara, Algolia and Custom Search search quality.

  Language:Ruby284101

• SeaseLtd/rated-ranking-evaluator

  Search Quality Evaluation Tool for Apache Solr & Elasticsearch search-based infrastructures

  Language:Java18037

• Yelp/xgboost-predictor-java

  Pure Java implementation of XGBoost predictor for online prediction tasks.

  Language:Java276

• THUxiexiaohui/SIGIR-2020-Tutorial

  Modeling User Behavior for Vertical Search: Images, Apps and Products

  81

• NTMC-Community/awesome-neural-models-for-semantic-match

  A curated list of papers dedicated to neural text (semantic) matching.

  Language:HTML774122

• NTMC-Community/MatchZoo

  Facilitating the design, comparison and sharing of deep text matching models.

  Language:Python3.8k898

• markovi/PyClick

  Language:Python273105

• varepsilon/clickmodels

  ClickModels is a small set of Python scripts for the user click models initially developed at Yandex. A Click Model is a probabilistic graphical model used to predict search engine click data from past observations. This project is aimed to deal with click models used in Information Retrieval (see next README.md) and intended to be easy-to-read and easy-to-modify. If it's not, please let me know how to improve it :)

  Language:Python23871

• wenyuer/POG

  the datasets of the paper POG

  769

• bmitra-msft/NDRM

  A repository for Neural Document Ranking Models.

  Language:Jupyter Notebook8527

• nmslib/nmslib

  Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.

  Language:C++3.4k450

• rspeer/python-ftfy

  Fixes mojibake and other glitches in Unicode text, after the fact.

  Language:Python3.8k121

• tensorflow/similarity

  TensorFlow Similarity is a python package focused on making similarity learning quick and easy.

  Language:Python1k103

• zurutech/anomaly-toolbox

  Anomaly detection using GANs.

  Language:Python9012

• openai/CLIP

  CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

  Language:Jupyter Notebook25.7k3.3k

• facebookresearch/fairseq

  Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

  Language:Python30.4k6.4k

• VinAIResearch/BERTweet

  BERTweet: A pre-trained language model for English Tweets (EMNLP-2020)

  Language:Python57352

• facebookresearch/NeuralDB

  Database Reasoning Over Text project for ACL paper

  Language:Python35348

• scikit-learn-contrib/hdbscan

  A high performance implementation of HDBSCAN clustering.

  Language:Jupyter Notebook2.8k502

• whylabs/whylogs

  An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈

  Language:Jupyter Notebook2.6k121

• facebookresearch/luckmatters

  Understanding Training Dynamics of Deep ReLU Networks

  Language:Python27631

• google-research/sloe-logistic

  Language:Python294

• linkedin/greykite

  A flexible, intuitive and fast forecasting library

  Language:Python1.8k105

• appsmithorg/appsmith

  Platform to build admin panels, internal tools, and dashboards. Integrates with 25+ databases and any API.

  Language:TypeScript34.3k3.7k

• dsternlicht/RESTool

  RESTool is an open source UI tool for managing RESTful APIs. It could save you time developing your own internal tools. A live example:

  Language:TypeScript479120

• facebookresearch/suncet

  Code to reproduce the results in the FAIR research papers "Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples" https://arxiv.org/abs/2104.13963 and "Supervision Accelerates Pre-training in Contrastive Semi-Supervised Learning of Visual Representations" https://arxiv.org/abs/2006.10803

  Language:Python48767

• facebookresearch/dino

  PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

  Language:Python6.3k909

• jupyterhub/repo2docker

  Turn repositories into Jupyter-enabled Docker images

  Language:Python1.6k362