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You’re caught in “tutorial hell” right now. The only way to get out is to build things and apply your knowledge. Easier said than done, obviously, but try out websites like Frontend Mentor to build your design and JS skills or apply to jobs on NoCSOK which is a site that’s emphasizes junior dev jobs that don’t require CS degrees. Source: over 2 years ago
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 / 13 days ago
Open the camera feed — and use the OpenCV library for real-time computer vision processing. - Source: dev.to / about 1 month 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 / 7 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
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Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
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Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
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NumPy - NumPy is the fundamental package for scientific computing with Python