https://github.com/theovidal/beta-project

🧠🧗‍♂️ Neural network to classify climbing routes
https://github.com/theovidal/beta-project

climbing neural-network

Last synced: about 1 month ago
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🧠🧗‍♂️ Neural network to classify climbing routes

• Host: GitHub
• URL: https://github.com/theovidal/beta-project
• Owner: theovidal
• License: gpl-3.0
• Created: 2020-11-11T18:15:28.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2024-08-29T19:35:26.000Z (5 months ago)
• Last Synced: 2024-08-29T21:48:56.138Z (5 months ago)
• Topics: climbing, neural-network
• Language: Jupyter Notebook
• Homepage:
• Size: 8.1 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        


    
Beta project

    
Using AI to classify climbing problems

    PDF



The project is a [Jupyter Notebook](./beta_project.ipynb) that contains a complete Data science methodology to analyse a simple yet interesting problem: route grades.

Climbing is a sportive discipline where participants must... climb, either indoor or outdoor. Here, we tackle indoor climbing: a wall contains holds, and the climber must only use some of them. A difficulty ("grade") is attributed following the pattern: (number in range 5-9)(letter in range a-c)(nothing or a + symbol) (for example: 5c+ or 8b).

The goal is to predict the grade of the route only using its physical properties, and not the feeling of the climber. We use Deep Learning algorithms inside a global Data science method to solve this problem.

Everything is printed in the [PDF file](./beta_project.pdf)

- [📜 Credits](#-credits)

- [🔐 License](#-license)

## 📜 Credits

- Data from [Moonboard](https://moonclimbing.com/moonboard)

## 🔐 License

[GNU GPL v3](./LICENSE)