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Table Of Contents
Machine Learning For Dummies
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Machine learning on images works because it can rely on features to compare pictures and associate an image with another one (because of similarity) or to a specific label (guessing, for instance, the represented objects). Humans can easily choose a car or a tree when we see one in a picture. Even if it’s the first time that we see a certain kind of tree or car, we can correctly associate it with the right object (labeling) or compare it with similar objects in memory (image recall).
In the case of a car, having wheels, doors, a steering wheel, and so on are all elements that help you categorize a new example of a car among other cars. It happens because you see shapes and elements beyond the image itself; thus, no matter how unusual a tree or a car may be, if it owns certain characteristics, you can figure out what it is.
An algorithm can infer elements (shapes, colors, particulars, relevant elements, and so on) directly from pixels only when you prepare...
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