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There are 17 posts tagged **maths** (this is page **2** of **2**).

This online course introduces the topic of modelling and simulating epidemics. If you are interested in understanding how Mathematicians, Programmers and Data Scientists are studying and fighting the spread of diseases, this series of posts is what you are looking for.

The third, and final part of this course will focus on different strategies that can be used to explore different mechanisms of transmission, and possible interventions.

- Part 1. The Mathematics of Epidemics
- Part 2. Simulating Epidemics
**Part 3. From an Outbreak to an Epidemic**

This online course is inspired by the recent COVID-19 pandemic. Now more than ever we need skilled and passionate people to focus on the complex subject of Epidemiology. I hope these articles will help some of you to get started.

All the revenue made from this article through Patreon will be donated to the National Emergencies Trust (NET) to help those most affected by the recent coronavirus outbreak. If you have recently become a patron for this reason, get in touch and I will add your contribution.

This is the second part of the online course dedicated to the modelling and simulating of epidemics. If you are interested in understanding how Mathematicians, Programmers and Data Scientists are studying and fighting the spread of diseases, this series of posts is what you are looking for.

In the second part, we will focus on ways to simulate epidemics. While the code here presented is in C# and runs in Unity, the knowledge can be applied to virtually any other language or engine.

You can read the rest of this online course here:

- Part 1. The Mathematics of Epidemics
**Part 2. Simulating Epidemics**- Part 3. From an Outbreak to an Epidemic

This online course is inspired by the recent COVID-19 pandemic. Now more than ever we need skilled and passionate people to focus on the complex subject of Epidemiology. I hope these articles will help some of you to get started.

And if you are interested in learning more about the virus responsible for the COVID-19 epidemics, SARS-CoV-2, have a look at the semi-serious video down below.

This online course introduces the topic of modelling and simulating epidemics. If you are interested in understanding how Mathematicians, Programmers and Data Scientists are studying and fighting the spread of diseases, this series of posts is what you are looking for.

**Part 1. The Mathematics of Epidemics**- Part 2. Simulating Epidemics
- Part 3. From an Outbreak to an Epidemic

This online course is inspired by the recent COVID-19 pandemic. Now more than ever we need skilled and passionate people to focus on the complex subject of Epidemiology. I hope these articles will help some of you to get started.

This tutorial will introduce the Transformation Matrix, one of the standard technique to translate, rotate and scale 2D graphics. The first part of this series, A Gentle Primer on 2D Rotations, explaines some of the Maths that is be used here.

- Introduction
- Part 1. Matrix notation
- Part 2. Adding translations
- Part 3. Composition
- Part 4. Inversion
- Part 5. Rotation around a point
- Conclusion

This post is for all the developers and mathematicians out there that are curious to explore and visualize the bizarre properties of numbers. Although Maths plays an important role in today’s technology, many people likes to ~~ab~~use it for **recreational purposes**. Part of the appeal of Recreational Maths lies in the challenge to discover something new. Despite what many believe, finding mathematical patterns is very easy; it’s discovering something useful that is incredibly challenging. If you’re up for such a challenge, this tutorial will teach you how to use Python to calculate some of the most ~~in~~famous numerical sequences.

- Part 0. Unlimited precision
- Part 1. Working with digits (Narcissistic numbers, Kaprekar numbers)
- Part 2. Working with sequences (Happy numbers)
- Part 3. Visualising graphs (Melancoil loop)
- Part 4. Parallel computation
- Conclusion

Randomness is so present in our reality that we are used to taking it for granted. Most of the phenomena which surround us have been generated by random processes. Hence, our brain is very good at recognising these *random patterns*. And it is even better at spotting phenomena that should be random but they actually aren’t. And this is when problems arise. Most software such as Unity or GameMaker simply lack the tools to generate *realistic* random numbers. This tutorial will introduce the Gaussian distribution, which plays a fundamental role in statistics since it is at the heart of many random phenomena in our everyday life.