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Mastering Java for Data Science

You're reading from   Mastering Java for Data Science Analytics and more for production-ready applications

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781782174271
Length 364 pages
Edition 1st Edition
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Author (1):
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Alexey Grigorev Alexey Grigorev
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Alexey Grigorev
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Deep learning for cats versus dogs


While MNIST is a very good dataset for educational purpose, it is quite small. Let's take a look at a different image recognition problem: given a picture, we want to predict if there is a cat on the image or a dog.

For this, we will use the dataset with dogs and cats pictures from a competition run on kaggle, and the dataset can be downloaded from https://www.kaggle.com/c/dogs-vs-cats.

Let's start by first reading the data.

Reading the data

For the dogs versus cats competition, there are two datasets; training, with 25,000 images of dogs and cats, 50% each, and testing. For the purposes of this chapter, we only need to download the training dataset. Once you have downloaded it, unpack it somewhere.

The filenames look like the following:

dog.9993.jpg dog.9994.jpg dog.9995.jpg

cat.10000.jpg cat.10001.jpg cat.10002.jpg

The label (dog or cat) is encoded into the filename.

As you know, the first thing we always do is to split the data into training and validation sets...

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