December 2018
Intermediate to advanced
274 pages
7h 46m
English
Content preview from Machine Learning for Mobile
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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.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.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.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.
What this book covers
Chapter 1, Introduction to Machine Learning on Mobile, explains what machine learning is and why we should use it on mobile devices. It introduces different approaches to machine learning and their pro and cons.
Chapter 2, Supervised and Unsupervised Learning Algorithms, covers supervised and unsupervised approaches of machine learning algorithms. We will also learn about different algorithms, such as Naive Bayes, decision trees, SVM, clustering, associated mapping, and many more.
Chapter 3, Random Forest on iOS, covers random forests and decision trees in depth and explains how to apply them to solve machine learning problems. We will also create an application using a decision tree to diagnose breast cancer.
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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.