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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Title
Step1:  Create Feature Matrix
Step2:  Add Interaction Features
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Python Code:
# Load libraries
from sklearn.preprocessing import PolynomialFeatures
import numpy as np
Explanation: Title: Create Interaction Features
Slug: create_interaction_features   
Summary: How to create interaction features for machine learning in Python. 
Date: 2016-09-06 12:00
Category: Machine Learning
Tags: Preprocessing Structured Data
Authors: Chris Albon
Preliminaries
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# Create feature matrix
X = np.array([[2, 3], 
              [2, 3], 
              [2, 3]])
Explanation: Create Feature Matrix
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# Create PolynomialFeatures object with interaction_only set to True
interaction = PolynomialFeatures(degree=2, interaction_only=True, include_bias=False)
# Transform feature matrix
interaction.fit_transform(X)
Explanation: Add Interaction Features
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