Contents

Introduction to Machine Learning

This tutorial would guide you to get started with the sklearn library to perfom machine learning. We’ll learn about important algorithms and methods to do supervised and unsupervised machine learning using different datasets. This tutorial is structured by topics that we’ll be covering; the navigation bar on the left has the list of topics. Below is an outline for all the sections.

Introduction to unsupervised learning: Introduction to unsupervised learning using kmeans clustering.

Introduction to supervised learning: Introduction to supervised learning using binary classification of protein sequences.

Introduction to PCA: Introduction to Principal Component Analysis for dimensionality reduction.

Throughout the tutorial, the python code is shown as a code block with grey background, e.g.

print("Hello World!")

Note

When you hover the mouse pointer over a code cell, there will be an option to copy the contents of that cell.