October 2016
Intermediate to advanced
558 pages
12h 39m
English
If you are familiar with the basics of machine learning, you will certainly know what supervised and unsupervised learning is all about. To give a quick refresher, supervised learning refers to building a function based on labeled samples. For example, if we are building a system to separate dress images from footwear images, we first need to build a database and label it. We need to tell our algorithm what images correspond to dresses and what images correspond to footwear. Based on this data, the algorithm will learn how to identify dresses and footwear so that when an unknown image comes in, it can recognize what's inside that image.
Unsupervised learning is the opposite of what we just discussed. ...
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