December 2018
Beginner to intermediate
226 pages
7h 59m
English
Content preview from Hands-On Meta Learning with Python
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Meta-SGD
Let's say we have some task, T. We use a model, 
, parameterized by some parameter, 
, and train the model to minimize the loss. We minimize the loss using gradient descent and find the optimal parameter 
for the model.
Let's recall the update rule of a gradient descent:
So, what are the key elements that make up our gradient descent? Let's ...
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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.