[PYTHON] Arrangement of self-mentioned things related to machine learning

Since it became difficult for me to understand what I wrote about machine learning, I made a list.

Many of the articles provide personal experience-based views on what will happen when doing machine learning with your own data. I don't fully understand the latest algorithms, so please read with a little discount.

-Importance of machine learning datasets -How to collect machine learning data -"Then, how does it compare to other methods?" -Machine learning library dlib -Machine learning library Shogun -Search for SVM -"OpenCV-Python Tutorials", "Practical Computer Vision" and scikit-learn -"OpenCV-Python Tutorials" and mahotas " -Try installing chainer-gogh --Translation Must-see "OpenCV-Python Tutorials" --Translation Must-see "OpenCV-Python Tutorials" 2 --Translation Face detection using Haar Cascades

-Tips for Python beginners to use the Scikit-image example for themselves -Tips for Python beginners to use the Scikit-image example for themselves 2 Process multiple files -[Tips 3 for Python beginners to use Scikit-image examples for themselves](Tips 3 for Python beginners to use Scikit-image examples for themselves) -Tips for Python beginners to use Scikit-image examples for themselves 4 Use GUI -Tips for Python beginners to use Scikit-image examples for themselves 5 Incorporate into network apps -Tips for Python beginners to use the Scikit-image example for themselves 6 Improve Python code -Tips for Python beginners to use the Scikit-image example for themselves 7 How to make a module -Tips for Python beginners to use the Scikit-image example for themselves 8 Processing time measurement and profiler -Tips for Python beginners to use the Scikit-image example for themselves 9 Use from C

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