How to streamline the implementation of reasoning systems with ReAgent from Facebook.
ReAgent is the end-to-end platform applied Reinforcement Learning designed for large-scale, distributed recommendation/optimization tasks where we don’t have access to a simulator. The main purpose of this framework is to make the development & experimentation of deep reinforcement algorithms fast. ReAgent is built on Python. It uses PyTorch framework for data modelling. ReAgent holds different algorithms for data preprocessing, feature engineering, model training & evaluation and lastly for optimized serving. It is capable of handling Large-dimension datasets, provides optimized algorithms for data preprocessing, training, and gives a highly efficient production environment for model serving. https://analyticsindiamag.com/hands-on-to-reagent-end-to-end-platform-for-applied-reinforcement-learning/