April 2020
Beginner to intermediate
156 pages
4h 47m
English
Content preview from Hands-On One-shot Learning with Python
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Section 2: Deep Learning Architectures
One-shot learning has been an active field of research for many scientists who are trying to find a cognitive machine that is as close as possible to humans in terms of learning. As there are various theories about how humans do one-shot learning, we have a lot of different deep learning methods that we can use to solve it. This section of the book will focus on metrics-based, model-based, and optimization-based deep learning architectures to tackle one-shot learning problems, along with their implementations.
This section comprises the following chapters:
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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.