Based on our record, OpenCV should be more popular than OpenAI Gym. It has been mentiond 50 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/). Source: 5 months ago
- [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 9 months ago
I came across a very interesting [project]( (4) Mckay Wrigley on Twitter: "My goal is to (hopefully!) add my house to the dataset over time so that I have an indoor assistant with knowledge of my surroundings. It’s basically just a slow process of building a good enough dataset. I hacked this together for 2 reasons: 1) It was fun, and I wanted to…" / X ) made by Mckay Wrigley and I was wondering what's the easiest... Source: 9 months ago
You also need C++ if you're going to do things which aren't built in as part of the engine. As an example if you're looking at using compute shaders, inbuilt native APIs such as a mobile phone's location services, or a third-party library such as OpenCV, then you're going to need C++. Source: 11 months 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: about 2 years ago
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
NumPy - NumPy is the fundamental package for scientific computing with Python
AWS DeepRacer - A 1/18th scale race car to learn machine learning 🚗