Introducing Reinforcement Learning Support with Amazon SageMaker RL
Amazon SageMaker now enables developers and data scientists to quickly and easily develop reinforcement learning models at scale with Amazon SageMaker RL.
In machine learning circles, there is a lot of buzz about reinforcement learning because it’s an exciting technology with a ton of potential. Reinforcement learning trains models without large amounts of training data, and it’s broadly useful when the reward function of a desired outcome is known but the path to achieving it is not and requires a lot of iteration to discover. Healthcare treatments, optimizing manufacturing supply chains, and solving gaming challenges are a few of the areas that reinforcement learning can help address. However, reinforcement learning has a steep learning curve and many moving parts, which effectively puts it out of the reach of all but the most well-funded and technical organizations. Amazon SageMaker RL, the cloud’s first managed reinforcement learning service, allows any developer to build, train, and deploy with reinforcement learning through managed reinforcement learning algorithms, support for multiple frameworks (including Intel Coach and Ray RL), multiple simulation environments (including MATLAB and Simulink), and integration with AWS RoboMaker, AWS’ new robotics service, which provides a simulation platform that integrates well with SageMaker RL.
Amazon SageMaker RL is now generally available in all AWS regions where Amazon SageMaker is available. Visit the product pages for more information.