OpenAI Gym VS NumPy

OpenAI Gym Reviews

NumPy Reviews

OpenAI Gym mentions (12)

• 5 Best Places to Use and Try AI Online

  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

• Why GPUs are great for Reinforcement Learning?

  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

• [D] Have there been successful applications of Deep RL to real problems other than board games/Atari?

  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

• Environments to Test Algorithms (Specifically Genetic Algorithms)

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

• [N] Gym now has a documentation website

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

NumPy mentions (107)

• Element-wise vs Matrix vs Dot multiplication

  In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 1 month ago

• JSON in data science projects: tips & tricks

  Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / about 2 months ago

• Introducing Flama for Robust Machine Learning APIs

  Numpy: A library for scientific computing in Python. - Source: dev.to / 4 months ago

• A Comprehensive Guide to NumPy Arrays

  Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago

• Beginning Python: Project Management With PDM

  A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago