Introduction to Scikit-learn
Chapter 1: Introduction
Introduction
Machine Learning (ML) will be central throughout your AI degree, whether you like it or not!
In this lesson, we will look at a machine learning library for Python called scikit-learn.
This lesson is NOT to teach you about machine learning (there is that other Introduction to Machine Learning module for that!) This is more of an introduction on how to use a Python library to perform machine learning.
I will assume that you already have some knowledge about machine learning. If you do not, you might want to wait until you have completed at least the first week of the Introduction to Machine Learning module.
Scikit-learn
Scikit-learn is built on NumPy, SciPy, Matplotlib and Pandas (this was why I introduced these first).
The name comes from the SciPy Toolkit (SciKit), because scikit-learn started out as a third party extension to SciPy. While we are not covering SciPy in our course, SciPy is essentially a library on top of NumPy that provides you with convenient classes and functions to perform scientific computations, like linear algebra, optimisation, and statistics.
In case you have not done so, you will need to install scikit-learn with pip install scikit-learn.
Are we ready?