Week 4

Introduction

This week will introduce some concepts from mathematics to help with understanding more advanced quantitative methods. We’re going to look at different types of functions including linear equations, and how to read and understand mathematical notation.

Below I’ve linked to resources which might be helpful if you want to brush up on some mathematics.

Learning Objectives

By the end of this week, you will be able to:

1. Define the concept of linear equations.
2. Compute simple linear algebra equations using vectors and matrices.
3. Translate mathematical equations into plain English.

Lecture

To access the lecture notes: Lecture

Quiz

To access the quiz on Moodle, please check Moodle page.

Practical

To access the practical:

1. Preview
2. Download

Note

To save a copy of notebook to your own GitHub Repo: follow the GitHub link, click on Raw and then Save File As... to save it to your own computer. Make sure to change the extension from .ipynb.txt (which will probably be the default) to .ipynbbefore adding the file to your GitHub repository.

Further resources

There are lot’s of introductory courses to linear algebra online, which might be helpful if you’re new to this type of maths.

• This linear algebra course from 3Blue1Brown covers some of the key ideas behind matrices: https://www.3blue1brown.com/topics/linear-algebra
• Alternatively there’s this Khan Academy course: https://www.khanacademy.org/math/linear-algebra

If you’re already familiar with linear algebra and you want to know more about how it relates to machine learning then you might find this book interesting - in particular Chapter 2: Mathematics for Machine Learning - Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong.