Zindi Competition Starter Notebooks and Solutions

This repository contains starter notebooks and solutions for various Zindi machine-learning competitions. The provided code and resources can serve as a learning resource for data science enthusiasts who want to understand different problem domains and learn about various machine learning techniques.

Inspiration

I've been competing on Zindi for a couple of years now and I remember always looking forward to starter notebooks from Johnathan Whitaker, I learned a lot from his notebooks and it helped shaped my learning. I hope this repository will help a lot of newbies as well.

Competitions Included

1. Busara Mental Health Prediction Challenge (IndabaX Nigeria)

   • Tags: Classification, Tabular

2. DataFest Africa Noise Pollution Classification Challenge

   • Tags: Audio, Deep Learning, Classification

3. DSN 2023 Bootcamp Qualification

   • Tags: Tabular, Regression

4. FREE AI Classes In Every City Hackathon

   • Tags: Tabular, Regression

5. GBV Hackathon

   • Tags: Text, Classification

6. Road Segment Identification Zindi

   • Tags: Images, Classification

7. SPEOAU Data Hackathon Starter Notebook

   • Tags: Tabular, Regression

8. Spot the Mask Challenge

   • Tags: Images, Classification

9. Swahili News Classification Challenge

   • Tags: Text, Classification

10. Task Mate Kenyan Sign Language Classification Challenge

    • Tags: Images, Classification

11. Turtle Recall Conservation Challenge

    • Tags: Images, Classification

12. UmojaHack 2023

    • Tags: Tabular, Classification

13. Umoja Hack Africa 2022

    • Tags: Tabular, Classification, Regression

14. Umoja Hack Main 2020

    • Tags: Tabular, Classification

Usage

Each competition folder contains a starter notebook and solutions related to that specific competition. To get started, follow the steps below:

1. Navigate to the competition folder of your choice.
2. Open the starter notebook to understand the problem and the dataset.
3. Explore the provided solutions to learn about different approaches and techniques.

Feel free to modify and adapt the code to suit your learning needs or even use it as a baseline for your own competition submissions.

License

This repository is licensed under the MIT License. You are free to use, modify, and distribute the code and resources as long as you provide proper attribution.

Contribution

If you would like to contribute to this repository by adding more starter notebooks, solutions, or improving existing ones, feel free to open pull requests. Your contributions are greatly appreciated and will help others in the community learn and grow.

Happy learning and happy coding!