Book Image

Building Machine Learning Systems with Python

Book Image

Building Machine Learning Systems with Python

Overview of this book

Machine learning, the field of building systems that learn from data, is exploding on the Web and elsewhere. Python is a wonderful language in which to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation and an increasing number of machine learning libraries are developed for Python.Building Machine Learning system with Python shows you exactly how to find patterns through raw data. The book starts by brushing up on your Python ML knowledge and introducing libraries, and then moves on to more serious projects on datasets, Modelling, Recommendations, improving recommendations through examples and sailing through sound and image processing in detail. Using open-source tools and libraries, readers will learn how to apply methods to text, images, and sounds. You will also learn how to evaluate, compare, and choose machine learning techniques. Written for Python programmers, Building Machine Learning Systems with Python teaches you how to use open-source libraries to solve real problems with machine learning. The book is based on real-world examples that the user can build on. Readers will learn how to write programs that classify the quality of StackOverflow answers or whether a music file is Jazz or Metal. They will learn regression, which is demonstrated on how to recommend movies to users. Advanced topics such as topic modeling (finding a text's most important topics), basket analysis, and cloud computing are covered as well as many other interesting aspects.Building Machine Learning Systems with Python will give you the tools and understanding required to build your own systems, which are tailored to solve your problems.
Table of Contents (20 chapters)
Building Machine Learning Systems with Python
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Loading and displaying images


In order to manipulate images, we will use a package called mahotas. This is an open source package (MIT license, so it can be used in any project) that was developed by one of the authors of the book you are reading. Fortunately, it is based on NumPy . The NumPy knowledge you have acquired so far can be used for image processing. There are other image packages such as scikit-image (Skimage), the ndimage (n-dimensional image) module in SciPy, and the Python bindings for OpenCV. All of these work natively with NumPy, so you can even mix and match functionalities from different packages to get your result.

We start by importing mahotas with the mh abbreviation, which we will use throughout this chapter:

import mahotas as mh

Now we can load an image file using imread:

image = mh.imread('imagefile.png')

If imagefile.png contains a color image of height h and width w, then image will be an array of shape (h, w, 3). The first dimension is the height, the second the width...