https://github.com/harrystaley/kaggle
A collection of projects and datasets used for Kaggle competitions, showcasing data analysis and machine learning solutions. Ideal for those interested in exploring and learning from real-world data challenges.
https://github.com/harrystaley/kaggle
competitions datasets kaggle
Last synced: 4 months ago
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A collection of projects and datasets used for Kaggle competitions, showcasing data analysis and machine learning solutions. Ideal for those interested in exploring and learning from real-world data challenges.
- Host: GitHub
- URL: https://github.com/harrystaley/kaggle
- Owner: harrystaley
- Created: 2022-02-23T00:24:24.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2025-04-12T09:10:07.000Z (over 1 year ago)
- Last Synced: 2025-04-12T10:24:08.709Z (over 1 year ago)
- Topics: competitions, datasets, kaggle
- Language: Jupyter Notebook
- Homepage:
- Size: 106 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Kaggle Repository
## Project Overview
This repository is a collection of projects and datasets used for Kaggle competitions. It showcases various data analysis and machine learning solutions. The projects and datasets in this repository are ideal for those interested in exploring and learning from real-world data challenges. Topics covered include Kaggle, competitions, and datasets.
## Setup and Installation
Before you start, ensure you have the following dependencies installed:
- Python 3.6 or later
- Jupyter Notebook
- Libraries: pandas, numpy, matplotlib, seaborn, scikit-learn
To clone and run this application, you'll need Git installed on your computer. From your command line:
```bash
# Clone this repository
$ git clone https://github.com/username/Kaggle.git
# Go into the repository
$ cd Kaggle
# Install dependencies
$ pip install -r requirements.txt
```
## Usage
After cloning the repository and installing the dependencies, you can open the Jupyter notebooks in the respective project folders.
For example, to run the Titanic project:
```bash
# Go into the Titanic project folder
$ cd Titanic
# Run Jupyter notebook
$ jupyter notebook
```
Then, navigate to the desired `.ipynb` file and open it. You can now interact with the code.
## Contribution Guidelines
We welcome contributions from everyone. If you're looking to contribute, please follow these steps:
1. Fork this repository.
2. Create your feature branch: `git checkout -b feature/your-feature-name`
3. Commit your changes: `git commit -m 'Add some feature'`
4. Push to the branch: `git push origin feature/your-feature-name`
5. Submit a pull request.
Please make sure your code complies with PEP8 and that your code changes do not break any existing functionalities of the projects.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE.md) file for details.