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Source channel @githubtrending · Post #15420 · Jan 18

#shell Try is a simple Ruby tool that organizes your coding experiments in one folder like ~/src/tries, using fuzzy search to quickly find or create dated directories (e.g., 2025-01-18-redis-test). Install via `gem install try-cli` or curl the single file, then add `eval "$(try init)"` to your shell—no setup needed. It ranks recent projects highest with smart matching, so you avoid scattered "test" folders and lost /tmp work. This saves time jumping between ideas, keeping your chaotic projects instantly accessible and productive. https://github.com/tobi/try

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djangoproject

@djangoproject · Post #507 · 11/26/2017, 10:08 PM

http://devarea.com/machine-learning-with-python-introduction/#.Whs6iCehU8o #Machine_Learning With Python – Introduction #Numpy is package for multi dimension arrays – very effective implementation #Scipy – package for scientific programming , mathematics , signal processing and more #Pandas – package for data handling #Matplotlib – package for data visualization (graphs) #Seaborn – extend Matplotlib with statistical graphs #Scikits – many extensions to spicy for specific fields like x-ray, image processing , deep learning and many more