Download
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like.
Features
- You can import the entire algorithm (say DDPG) and tell it to ddpg.learn(batch), you can import networks and the learning function separately, create a custom loader for your task, or can define everything by yourself
- Examples do not contain any of the junk code or workarounds: pure model definition and the algorithm itself in one file. I wrote a couple of articles explaining how it functions
- Documentation available
- The learning is built around sequential or frame environment that supports ML20M and like
- Seq and Frame determine the length type of sequential data, seq is fully sequential dynamic size (WIP), while the frame is just a static frame
- State Representation module with various methods. For sequential state representation, you can use LSTM/RNN/GRU (WIP)
- Parallel data loading with Modin (Dask / Ray) and caching
- Pytorch 1.7 support with Tensorboard visualization.
Project Samples
Categories
Libraries, Reinforcement Learning Frameworks, Reinforcement Learning Libraries, Reinforcement Learning AlgorithmsLicense
Apache License V2.0Follow RecNN
Other Useful Business Software
MongoDB Atlas runs apps anywhere
MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of RecNN!
