Learning Data Mining with Python

Chapter 1
In the preceding dataset, we had an obvious feature type. We wanted to know if
people are short or tall, so we collected their heights. This engineering feature is an
important problem in data mining. In later chapters, we will discuss methods for
choosing good features to collect in your dataset. Ultimately, this step often requires
some expert domain knowledge or at least some trial and error.
In this book, we will introduce data mining through Python. In some
cases, we choose clarity of code and workflows, rather than the most
optimized way to do this. This sometimes involves skipping some
details that can improve the algorithm's speed or effectiveness.
Using Python and the IPython Notebook
In this section, we will cover installing Python and the environment that we will use
for most of the book, the IPython Notebook. Furthermore, we will install the numpy
module, which we will use for the first set of examples.
Installing Python
The Python language is a fantastic, versatile, and an easy to use language.
For this book, we will be using Python 3.4, which is available for your system from
the Python Organization's website: https://www.python.org/downloads/.
There will be two major versions to choose from, Python 3.4 and Python 2.7.
Remember to download and install Python 3.4, which is the version tested
throughout this book.
In this book, we will be assuming that you have some knowledge of programming
and Python itself. You do not need to be an expert with Python to complete this
book, although a good level of knowledge will help.
If you do not have any experience with programming, I recommend that you
pick up the Learning Python book from.
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