Rivet

RIVET is a tool for Topological Data Analysis, in particular two-parameter persistent homology.

Data ScienceC++GPL-3.0

Abstract

Rivet is an open-source Data Science project. RIVET is a tool for Topological Data Analysis, in particular two-parameter persistent homology. Program for the visualization and analysis of two-parameter persistent homology. It is built using C++. The complete source code is publicly available on GitHub under the GNU General Public License v3.0, making it a useful reference for students building a Data Science mini project or final-year project.

1. Introduction

Program for the visualization and analysis of two-parameter persistent homology.

2. Objective

RIVET is a tool for Topological Data Analysis, in particular two-parameter persistent homology.

This project demonstrates how C++ can be applied to a real-world Data Science problem.

4. Technology Stack

C++

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

  • Arduino IDE / PlatformIO or a C++ compiler (g++)
  • Target board (e.g. Arduino, ESP32) where applicable
  • Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/rivetTDA/rivet.git
cd rivet

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

  • Turn the analysis into an interactive dashboard
  • Automate data refresh with a scheduled job
  • Add a predictive model on top of the analysis

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

  1. What is the source of the dataset and how was missing data handled?
  2. Which exploratory analysis steps revealed the most useful insight?
  3. Why were these particular charts chosen to present the data?
  4. Which statistical or ML technique supports the conclusions?
  5. How could the analysis be automated or refreshed with new data?

9. Source Code & License

This project is developed by rivetTDA and published on GitHub under the GNU General Public License v3.0. Please follow the license terms and credit the original author when you use or modify this code.

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