Which cloud service is used as a teaching tool for reinforcement learning?

AWS DeepRacer is specifically designed as a teaching tool for reinforcement learning, providing a hands-on approach to learning this complex area of artificial intelligence. It allows users to train reinforcement learning models through a racing simulation environment where they can experiment with different algorithms and strategies for improving performance. This hands-on learning experience is particularly beneficial because it combines practical engagement with theoretical principles of reinforcement learning.

The other options, while related to machine learning and data processing, serve different purposes. Cloud AutoML is focused on automating the process of building machine learning models, rather than specifically teaching reinforcement learning. Watson OpenScale offers tools for monitoring and ensuring the trustworthiness of AI models, which does not align with the educational focus of AWS DeepRacer. Azure Databricks provides an environment for running big data analytics and machine learning, but it is not tailored exclusively for reinforcement learning education in the way AWS DeepRacer is designed to do. Thus, AWS DeepRacer stands out as the most suitable choice for teaching reinforcement learning.