Chapter 1. Getting Started with Data Mining
We are collecting information at a scale that has never been seen before in the history of mankind and placing more day-to-day importance on the use of this information in everyday life. We expect our computers to translate Web pages into other languages, predict the weather, suggest books we would like, and diagnose our health issues. These expectations will grow, both in the number of applications and also in the efficacy we expect. Data mining is a methodology that we can employ to train computers to make decisions with data and forms the backbone of many high-tech systems of today.
The Python language is fast growing in popularity, for a good reason. It gives the programmer a lot of flexibility; it has a large number of modules to perform different tasks; and Python code is usually more readable and concise than in any other languages. There is a large and an active community of researchers, practitioners, and beginners using Python for data mining.
In this chapter, we will introduce data mining with Python. We will cover the following topics:
- What is data mining and where can it be used?
- Setting up a Python-based environment to perform data mining
- An example of affinity analysis, recommending products based on purchasing habits
- An example of (a classic) classification problem, predicting the plant species based on its measurement
