February 2018
Intermediate to advanced
378 pages
10h 14m
English
Content preview from Machine Learning with Swift
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Summary
In this chapter, we learned about the main concepts in ML .
We discussed different definitions and subdomains of artificial intelligence, including ML . ML is the science and practice of extracting knowledge from data. We also explained the motivation behind ML . We had a brief overview of its application domains: digital signal processing, computer vision, and natural language processing.
We learned about the two core concepts in ML : the data, and the model. Your model is only as good as your data. A typical ML dataset consists of samples; each sample consists of features. There are many types of features and many techniques to extract useful information from the features. These techniques are known as feature engineering. For supervised ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.