January 2018
Intermediate to advanced
470 pages
11h 9m
English
Content preview from Scala Machine Learning Projects
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Image classification and drawbacks of DNNs
Before we start developing the end-to-end project for image classification using CNN, we need some background studies, such as the drawbacks of regular DNNs, suitability of CNNs over DNNs for image classification, CNN constructions, CNN's different operations, and so on. Although regular DNNs work fine for small images (for example, MNIST, CIFAR-10), it breaks down for larger images because of the huge number of parameters it requires. For example, a 100 x 100 image has 10,000 pixels, and if the first layer has just 1,000 neurons (which already severely restricts the amount of information transmitted to the next layer), this means a total of 10 million connections. And that's just for the first layer. ...
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