February 2018
Intermediate to advanced
378 pages
10h 14m
English
Content preview from Machine Learning with Swift
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Mobile versus server-side ML
Most Swift developers are writing their applications for iOS. Those among us who develop their Swift applications for macOS or server-side are in a lucky position regarding ML . They can use whatever libraries and tools they want, reckoning on powerful hardware and compatibility with interpretable languages. Most of the ML libraries and frameworks are developed with server-side (or at least powerful desktops) in mind. In this book, we talk mostly about iOS applications, and therefore most practical examples consider limitations of handheld devices.
But if mobile devices have limited capabilities, we can do all ML on the server-side, can't we? Why would anyone bother to do ML locally on mobile devices at all? There ...
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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.