December 2018
Intermediate to advanced
274 pages
7h 46m
English
Content preview from Machine Learning for Mobile
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Spam Message Detection
This chapter will provide you with an overview of natural language processing (NLP) and discuss how NLP can be combined with machine learning to provide solutions to problems. Then, the chapter will take a real-world use case of doing spam message detection by utilizing NLP, combined with the linear SVM classification model. The program will be implemented as a mobile application using Core ML for iOS.
To handle text in machine learning algorithms, we will go through the various NLP techniques that will be used on the text data to make it ready for learning algorithms. Once the text is prepared, we will see how we can classify it using the linear SVM model.
Problem definition: The bulk SMS message data is provided, ...
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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.