May 2019
Intermediate to advanced
162 pages
4h 24m
English
Content preview from Supervised Machine Learning with Python
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Parametric models
When it comes to supervised learning, there are two families of learning algorithms: parametric and non-parametric. This area also happens to be a hotbed for gatekeeping and opinion-based conjecture regarding which is better. Basically, parametric models are finite-dimensional, which means that they can learn only a defined number of model parameters. Their learning stage is typically categorized by learning some vector theta, which is also called a coefficient. Finally, the learning function is often a known form, which we will clarify later in this section.
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.