Beast code in Giters

Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR and CVR prediction), Post Ranking, Multi-task Learning, Graph Neural Networks, Transfer Learning, Reinforcement Learning, Self-supervised Learning and so on.

Language:Python1306 50 1

marp-core

The core of Marp converter

Language:TypeScriptMIT728 10 85

ReChorus

“Chorus” of recommendation models: a light and flexible PyTorch framework for Top-K recommendation.

Language:PythonMIT493 14 43

qtrader

A Light Event-Driven Algorithmic Trading Engine

Language:Python430 16 24

basana

A Python async and event driven framework for algorithmic trading, with a focus on crypto currencies.

Language:PythonNOASSERTION426 15 15

torch-rechub

A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.

Language:PythonMIT357 12 21

remark-it

markdown -> slideshow ——Write PPT like a programmer

Language:CSSMIT159 5 12

DBRL

Dataset Batch(offline) Reinforcement Learning for recommender system

Language:Python141 3 9

classix

Fast and explainable clustering in Python

Language:PythonMIT96 2 13

Torch-RecHub

A Lighting Pytorch Framework for Recommendation System, Easy-to-use and Easy-to-extend.

Language:PythonMIT78 20

backtester

An event-driven backtester

Language:Python75 9 1

recommendation_system_sort_model

推荐系统排序模型复现

Language:Jupyter Notebook42 1 7

fABBA

A Python library for the fast symbolic approximation of time series

Language:PythonBSD-3-Clause39 2 4

PyUPPAAL

A research tool that can modify and verify UPPAAL models with python. It can also help to parse counter-examples, or find all possible patterns of a UPPAAL property.

Language:PythonMIT2700