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Population Modeling and Simulations in Python

PROJECT


Population Modeling and Simulations in Python

In this project, we’ll learn to use concepts of mathematics and business to create simulations and aid the process of decision-making.

Population Modeling and Simulations in Python

You will learn to:

Understand modeling and simulations.

Create John Conway's Game of Life.

Run the Lotka-Volterra model.

Make epidemiology modeling programs.

Create interactive data visualizations.

Serve simulations in the browser.

Skills

Python Programming

Mathematical Animation

Modeling and Simulation

Prerequisites

Intermediate proficiency in Python

Basic knowledge of calculus

Basic knowledge of data visualization

Technologies

NumPy

SciPy

Plotly

Pandas

Matplotlib

Project Description

One of the main limitations of the current state of machine learning and deep learning is the constant need for new data. How can we make predictions when we don’t have any data available? This lack of data is more common than we would normally think.

In this project, we’ll learn about modeling and simulations and how they can be applied in various population analysis scenarios, such as understanding how diseases can spread within a community, prey/predator dynamics, and Conway’s Game of Life. Throughout the project, we will make sure that everything is interactive and shareable on the web. To do so, we will learn to use libraries such as SciPy, Matplotlib, Plotly, Streamlit, Datapane, and others.

Project Tasks

1

Introduction

Task 0: Getting Started

2

Game of Life

Task 1: Creating John Conway’s Game of Life

Task 2: Comparing and Animating Game of Life

3

Lotka-Volterra Model

Task 3: Introduction to Lotka-Volterra Model

Task 4: Creating a Phase-Space Plot

Task 5: Making Visualizations Interactive

Task 6: Adding Logistic Growth

Task 7: Creating a LG Summary Interactive Plot

Task 8: Finding LG Steady State

Task 9: Implementing Parameter Fitting

Task 10: Exploring Euler's Method

4

Epidemiology Modeling

Task 11: Making an SIR Model

Task 12: Deriving SIR Phase-Space Plot

Task 13: Adding the Time-Limited Immunity

Task 14: Making SIR Stochastic

Task 15: Implementing Agent Based Modeling

Task 16: Adding Space Plotting in Agent Based Modeling

5

Web Sharing

Task 17: Exploring Streamlit

Task 18: Exploring Datapane

Task 19: Exploring PyScript

6

Congratulations!

Congratulations!

has successfully completed the Guided ProjectPopulation Modeling and Simulations in Python

Relevant Courses

Use the following content to review prerequisites or explore specific concepts in detail.