Cancer Dataset Analysis 🧬

About

In this project, we are going to plot our cancer dataset in graph form and also find out precision, recall, accuracy, and predictions.

Table of Contents

• Installation ⚙️
• Usage 🚀
• Examples 📊
• Contributing 🤝
• License 📜
• Contact 📬
• Socials 🌐

Installation ⚙️

1. Clone the repository:

   git clone https://github.com/SyedMuqtasidAli/cancer-dataset-analysis.git

2. Navigate to the project directory:

   cd cancer-dataset-analysis

3. Install the required dependencies:

   pip install -r requirements.txt

Usage 🚀

Open the Jupyter Notebook file cancer_detection.ipynb to run the analysis.

1. Launch Jupyter Notebook:

   jupyter notebook

2. Open the cancer_detection.ipynb file and execute the cells to perform the analysis and visualize the data.

Examples 📊

Here are a few examples of what you can do with this project:

1. Plotting the Data:

   • The notebook includes code to plot various aspects of the cancer dataset, such as distributions and correlations.

2. Model Evaluation:

   • You can evaluate models by calculating precision, recall, accuracy, and making predictions.

Contributing 🤝

Contributions are welcome! Please fork the repository and submit a pull request with your improvements.

1. Fork the repository
2. Create a new branch (git checkout -b feature-branch)
3. Commit your changes (git commit -am 'Add new feature')
4. Push to the branch (git push origin feature-branch)
5. Create a new Pull Request

License 📜

This project is licensed under the MIT License. See the LICENSE file for more details.

Contact 📬

For any questions or suggestions, feel free to reach out:

Socials 🌐

Stay connected and follow for more updates:

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Happy coding! 💻