Who This Book Is For
This book is intended for Python programmers who want to add Machine Learning to their repertoire, either for a specific project or as part of keeping their toolkit relevant. Perhaps a new problem has come up at work that requires machine learning. With machine learning being covered so much in the news
these days, it’s a useful skill to claim on a resume.
This book provides the following for Python programmers:
- A description of the basic problems that machine learning attacks.
- Several state-of-the-art algorithms.
- The principles of operation for these algorithms.
- Process steps for specifying, designing, and qualifying a machine learning system.
- Examples of the processes and algorithms.
- Hackable code
What You Need to Use This Book
To run the code examples in the book, you need to have Python 2.x, SciPy, NumPy, Pandas, and scikit-learn. These can be difficult to install due to cross-dependencies and version issues. To make the installation easy, I’ve used a free distribution of these packages that are available from Continuum Analytics (http://continuum.io/). Their Anaconda product is a free download and includes Python 2.x and all the packages you need to run the code in this book (and more). I’ve run the examples on Ubuntu 14.04 Linux but haven’t tried them on other operating systems.
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