Understanding the scikit-learn library

In this section, we will look at the scikit-learn library and will use it to implement a simple predictive model. To do this, we need to understand scikit-learn and how to load the iris dataset to the Jupyter Notebook. We will then take a closer look at how to build a supervised machine learning model using scikit-learn and, using this, we will build a simple predictive model. 

 

scikit-learn

scikit-learn is the most popular Python library for doing machine learning. It provides a simple and efficient API with tools for data modeling and data analysis. It is built on top of NumPy, SciPy, and Matplotlib. The following is a screenshot of a Jupyter Notebook: 

We do not import the entire library, but instead we import the ones we really need. We need to import the datasets objects. This allows us to load all the datasets that scikit-learn provides. 

To understand the concept better, we will use the example of the iris dataset. This runs parallel to the hello...