allRank

Ranking framework

A framework for training neural models to rank data items based on relevance

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

GitHub

871 stars
28 watching
119 forks
Language: Python
last commit: 4 months ago
Linked from 1 awesome list

click-modeldeep-learninginformation-retrievallearning-to-rankmachine-learningndcgpythonpytorchrankingtransformer

Backlinks from these awesome lists:

Related projects:

Repository Description Stars
kengz/slm-lab A comprehensive framework for deep reinforcement learning using PyTorch. 1,256
erotemic/netharn A PyTorch framework for managing and automating deep learning training loops with features like hyperparameter tracking and single-file deployments. 39
achaiah/pywick A PyTorch-based neural network training framework with advanced features and utilities 398
asappresearch/flambe An ML framework for accelerating research and its integration into production workflows 262
oml-team/open-metric-learning A PyTorch-based framework for training and validating models that produce high-quality embeddings for computer vision and other tasks. 882
metarank/metarank A low-code, scalable Machine Learning service for building personalized search and recommendations rankings 2,085
unslothai/hyperlearn An optimized machine learning framework using PyTorch that improves performance and efficiency on various hardware configurations 1,842
astooke/rlpyt A modular and unified framework for implementing common deep reinforcement learning algorithms in PyTorch 2,232
tristandeleu/pytorch-maml-rl Replication of Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks in PyTorch for reinforcement learning tasks 827
alibaba/easyrec A framework for building and deploying scalable recommendation algorithms 1,784
gudovskiy/autodo Develops an automated machine learning framework to improve deep learning model performance on biased and noisy data 24
ramon-oliveira/aorun A deep learning framework on top of PyTorch for building neural networks. 61
hpclab/quickrank A collection of efficient Learning-to-Rank algorithms implemented in C++ 131
microsoft/archai Automates the search for optimal neural network configurations in deep learning applications 467
mauriziofd/recsys2019_deeplearning_evaluation An evaluation framework and repository of deep learning algorithms for recommendation systems 983