While KotlinDL seems to be a good solution by Jetbrains, I would personally stick to Java frameworks like DL4J for a better community support and likely more features. Source: almost 3 years ago

Would recommend taking a look at dl4j: https://deeplearning4j.org. Source: about 3 years ago

We use DeepLearning4j in this chapter because it is written in Java and easy to use with Clojure. In a later chapter we will use the Clojure library libpython-clj to access other deep learning-based tools like the Hugging Face Transformer models for question answering systems as well as the spaCy Python library for NLP. Source: about 3 years ago

FastAPI. Or even simpler: DL4J, to be used in Java when we need to communicate with the rest of the applications in real time. Source: about 3 years ago

OpenAI Gym: If you're interested in using AI for machine learning, OpenAI Gym (https://gym.openai.com/) is a great resource. It's a platform that provides a wide range of environments and tools for developing and testing machine learning algorithms. You can use it to experiment with different techniques and see how well they perform. Source: over 1 year ago

Open source toolkits such as Open AI Gym can be used for developing and comparing reinforcement learning algorithms. - Source: dev.to / about 2 years ago

There is a lot of work in games, particularly board games, but these do not really solve something "useful" for society. I have seen also lots of toy examples with libraries like gym and some robotics but in general these are rather proof-of-concept models or just models that do not work at all. One that actually does work is Solving Rubik’s Cube with a Robot Hand. This is pretty cool, but again, the domain... Source: about 2 years ago

I haven't used it, but assume https://gym.openai.com/ is exactly for this. Source: about 2 years ago

I know it's not a good website but I thought https://gym.openai.com/ was the documentation, is it not? Source: over 2 years ago