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Learning Data Mining with Python

Learning Data Mining with Python

By : Robert Layton
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Learning Data Mining with Python

Learning Data Mining with Python

By: Robert Layton

Overview of this book

This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK. You will gain hands on experience with complex data types including text, images, and graphs. You will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now. With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining and understanding of the algorithms as well as implementations.
Table of Contents (14 chapters)
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Application


Back on your main computer now, open the first Jupyter Notebook we created in this chapter—the one that we loaded the CIFAR dataset with. In this major experiment, we will take the CIFAR dataset, create a deep convolution neural network, and then run it on our GPU-based virtual machine.

 

Getting the data

To start with, we will take our CIFAR images and create a dataset with them. Unlike previously, we are going to preserve the pixel structure—that is, in rows and columns. First, load all the batches into a list:

import os
import numpy as np 

data_folder = os.path.join(os.path.expanduser("~"), "Data", "cifar-10-batches-py")

batches = [] 
for i in range(1, 6):
    batch_filename = os.path.join(data_folder, "data_batch_{}".format(i))
    batches.append(unpickle(batch_filename)) 
    break

The last line, the break, is to test the code—this will drastically reduce the number of training examples, allowing you to quickly see if your code is working. I'll prompt you later to remove this...

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