Based on our record, OpenCV should be more popular than QuantConnect. It has been mentiond 51 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.
Open the camera feed — and use the OpenCV library for real-time computer vision processing. - Source: dev.to / 8 days ago
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 / 6 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: 6 months ago
- [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 10 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: 10 months ago
I use https://quantconnect.com/ to backtest new algos and discover new algos. They support C# and python. Source: over 1 year ago
Use quantconnect.com, their API forces you to use OOP there so it's a good practice. Source: almost 2 years ago
For stocks and crypto: QuantConnect and Backtrader For options: MesoSim and OptionNetExplorer. Source: almost 2 years ago
Only you can teach you how to do it. quantconnect.com has a lot of tutorials and other documentation that should be enough for you to learn from. I'm still learning the process of backtesting and I'm not aware of an "easy" way to perform this type of work. Source: almost 2 years ago
Thanks for the pointer. quantconnect.com and interactive brokers. I have a little fantasy that I'll do this once I retire and hand over 1% of my nest egg to it; see how it does... Hand over some more, etc... Source: over 2 years ago
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
CloudQuant - Crowd based algorithmic trading development and backtesing for stock market trading.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
quantra - A public API for quantitative finance made with Quantlib
NumPy - NumPy is the fundamental package for scientific computing with Python
Backtrader - Backtrader is a complete and advanced python framework that is used for backtesting and trading.