December 2018
Beginner to intermediate
226 pages
7h 59m
English
Content preview from Hands-On Meta Learning with Python
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Algorithm
Now we'll see how our algorithm works step by step:
- Let's say we've a task distribution
. First, we randomly initialize our model parameters such as a parameter of concept generator 
, meta learner 
, and concept discriminator 
. - We sample a batch of tasks from the task distributions and learn their concepts via the concept generator, perform ...
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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.