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The purpose of this Personalized Music Recommendation Engine is to use reinforcement learning approach to build a music recommender system and to formulate the problem of interactive recommendation as a contextual multi-armed bandit, learning user preferences recommending new songs and receiving their ratings.
This is the implementation of RL4Rec
A high-performance distributed training framework for Reinforcement Learning
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation
Reinforcement learning algorithms for recommendation.
Reinforced Recommendation toolkit built around pytorch 1.7
Reinforcement Learning BPMF Highway_network
Explore the potential of recommendation system using reinforcement learning
The implemetation of Deep Reinforcement Learning based Recommender System from the paper Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling by Liu et al.
Course project for https://deeppavlov.ai/rl_course_2020
Reproduce of Top-K Off-Policy Correction for a REINFORCE Recommender System
The purpose of our research is to study reinforcement learning approaches to building a movie recommender system. We formulate the problem of interactive recommendation as a contextual multi-armed bandit.
Recommendation System using Deep Q-Networks and Double Deep Q-Networks
RL Recommendation System
paper list in the area of reinforcenment learning for recommendation systems
reinforcement learning for recommendation systems.
Train auto_car in CARLA simulator with RL algorithms(SAC).
Project for Course : Reinforcement Learning
A comparison of Google SlateQ algorithm with traditional Reinforcement Learning algorithms
Reproducing YouTube's slateQ algorithm described in the paper: https://arxiv.org/pdf/1905.12767.pdf optimizing the top-k recommendation experience for long term engagement.
The code to reproduce the experimental results for "A Text-based Deep Reinforcement Learning Framework for Interactive Recommendation".
Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学
机器学习相关教程
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Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
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Some thing interesting about visualization, use data art
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We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.