October 2017
Beginner to intermediate
270 pages
7h
English
Content preview from Machine Learning for Developers
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Events
In order to understand probabilities, we first need to define events. An event is, given an experiment in which we perform a determined action with different possible results, a subset of all the possible outcomes for that experiment.
Examples of events are a particular dice number appearing, and a product defect of particular type appearing on an assembly line.
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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.