November 2018
Intermediate to advanced
300 pages
7h 42m
English
Content preview from Machine Learning in Java - Second Edition
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Building a single-layer regression model
Let's start by building a single-layer regression model based on the softmax activation function, as shown in the following diagram. As we have a single layer, Input to the neural network will be all the figure pixels, that is, 28 x 28 = 748 neurons. The number of Output neurons is 10, one for each digit. The network layers are fully connected, as shown in the following diagram:
A neural network is defined through a NeuralNetConfiguration.Builder() object as follows:
MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
We will define the parameters for gradient search in order to 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.