August 2018
Intermediate to advanced
334 pages
7h 20m
English
Content preview from Applied Deep Learning with Python
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Regularization Strategies
Neural networks are particularly prone to overfitting. Overfitting happens when a network learns the patterns of the Neural networks are particularly prone to overfitting. Overfitting happens when a network learns the patterns of the training data but is unable to find generalizable patterns that can also be applied to the test data.he training data but is unable to find generalizable patterns that can also be applied to the test data.
Regularization strategies refer to techniques that deal with the problem of overfitting by adjusting how the network learns. In this book, we discuss two common strategies: L2 and Dropout.
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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.Julian F.
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.Addison B.
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.Amir M.
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.