Python Machine Learning Cookbook

Preprocessing data using different techniques

In the real world, we usually have to deal with a lot of raw data. This raw data is not readily ingestible by machine learning algorithms. To prepare the data for machine learning, we have to preprocess it before we feed it into various algorithms.

Getting ready

Let's see how to preprocess data in Python. To start off, open a file with a .py extension, for example, preprocessor.py, in your favorite text editor. Add the following lines to this file:

import numpy as np
from sklearn import preprocessing

We just imported a couple of necessary packages. Let's create some sample data. Add the following line to this file:

data = np.array([[3, -1.5,  2, -5.4], [0,  4,  -0.3, 2.1], [1,  3.3, -1.9, -4.3]])

We are now ...