December 2017
Intermediate to advanced
536 pages
14h 23m
English
Content preview from TensorFlow 1.x Deep Learning Cookbook
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How it works...
Using ConvNets, we increased our performance on the MNIST dataset reaching almost 95 percent accuracy. Our ConvNet consists of two layers combining convolutions, ReLU, and maxpooling, followed by two fully connected layers with dropout. Training happens in batches of size 128 with Adam used as an optimizer, a learning rate of 0.001, and a maximum number of 500 iterations.
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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.