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This repository is a collection of useful jupyter notebooks, code snippets and example JSON files illustrating the use of Reinvent 3.2.
Features
- Full-fledged use case using public data on DRD2, including use of predictive models and elucidating general considerations
- Explanation on how to initialize a new model (prior / agent) for REINVENT which can be trained in a transfer learning setup
- Tutorial on how to prepare (clean, filter and standardize) data from a source such as ChEMBL to be used for training
- Shows how to train a predictive (QSAR) model to be used with REINVENT based on the public DRD2 dataset (classification problem)
- Example reinforcement learning run with a selection of scoring function components to generate novel compounds with ever higher scores iteratively
- Very simple (only 1, easy-to-understand component) transfer learning example
Project Samples
Categories
Libraries, Reinforcement Learning Frameworks, Reinforcement Learning Libraries, Reinforcement Learning AlgorithmsLicense
MIT LicenseFollow ReinventCommunity
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