Based on our record, OpenCV should be more popular than Deepnote. It has been mentiond 52 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.
How to Accomplish: Use statistical analysis tools and libraries (e.g., Pandas for tabular data) to calculate and visualize these characteristics. For image datasets, custom scripts to analyze object sizes or mask distributions can be useful. Tools like OpenCV can assist in analyzing image properties, while libraries like Pandas and NumPy are excellent for tabular and numerical analysis. To address class... - Source: dev.to / 4 days ago
Open the camera feed — and use the OpenCV library for real-time computer vision processing. - Source: dev.to / 28 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: 7 months ago
- [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 11 months ago
Deepnote - A new data science notebook. Jupyter is compatible with real-time collaboration and running in the cloud. The free tier includes unlimited personal projects, up to 750 hours of standard hardware, and teams with up to 3 editors. - Source: dev.to / 4 months ago
We looked into many of these issues with Deepnote (YC S19) [https://deepnote.com/]. What we found is that these are not necessarily problems of the underlying medium (a notebook), but more of the specific implementation (Jupyter). We've seen a lot of progress in the Jupyter ecosystem, but unfortunately almost none in the areas you mentioned. - Source: Hacker News / about 1 year ago
Upload your ipynb to Deepnote and publish as an app. That simple. https://deepnote.com. - Source: Hacker News / about 1 year ago
Using Deepnote, we'll create a Python notebook and upload the two GeoJSON files into a data directory. - Source: dev.to / over 1 year ago
Deepnote - A new kind of data science notebook. Jupyter-compatible with real-time collaboration and running in the cloud. Free tier includes unlimited personal projects, up to 750 hours of standard hardware and teams with up to 3 editors. - Source: dev.to / over 1 year ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Apache Zeppelin - A web-based notebook that enables interactive data analytics.
NumPy - NumPy is the fundamental package for scientific computing with Python
Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.