February 2019
Intermediate to advanced
260 pages
6h 3m
English
Content preview from Hands-On Java Deep Learning for Computer Vision
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Building a handwritten digit recognizer
By building a handwritten digit recognizer in a Java application, we will practically implement most of the techniques and optimizations learned so far. The application is built using the open source Java framework, Deeplearning4j. The dataset used is the classic MNIST database of handwritten digits. (http://yann.lecun.com/exdb/mnist/). The training dataset is oversized, having 60,000 images, while the test data set contains 10,000 images. The images are 28 x 28 in size and grayscale in terms of terms.
As a part of the application that we will be creating in this section, we will implement a graphical user interface, where you can draw digits and get a neural network to recognize the digit.
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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.