Machine Learning Projects Repository 🐍🪄✨

Welcome to the Machine Learning Projects repository! 🚀 This repository contains various machine learning projects implemented with clean code, detailed explanations, and a structured approach.

Table of Contents

1. Overview
2. Project List
3. Technologies Used
4. How to Use
5. Installation
6. Contributing
7. Contact

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Overview

This repository is a collection of machine learning projects showcasing:

• Data preprocessing
• Model building and evaluation
• Visualization of results

Each project is designed to address real-world problems and demonstrate practical applications of machine learning techniques.

Project List

Below are the projects included in this repository:

1. Project 1: [Diabities Prediction]

   • [View Project Folder]

2. Project 2: [Mobile Price Prediction]

   • [View Project Folder]

3. Project 3: [Chest Disease Classification]

   • [View Project Folder]

4. Project 4: [Hand-Controlled-Screenshot]

   • [View Project Folder]

5. Project 5: [Customer-Purchase-Prediction]

   • View Project Folder

6. Project 6: [Heart-Disease-Prediction]

   • View Project Folder

7. Project 7: [Face-Emotion-Classification-Using-FER-Dataset]

   • [View Project Folder]

8. Project 8: [K-means-Algorithm]

   • [View Project Folder]

9. Project 9: [Sarcasm-Detection]

   • [[View Project Folder]]

Technologies Used:

The following tools and libraries are used across the projects:

• Python: Core programming language 💗
• Libraries:
  • NumPy
  • Pandas
  • Matplotlib
  • Scikit-learn
  • TensorFlow/PyTorch

How to Use:

To explore and run the projects:

1. Clone the repository to your local machine:

   git clone https://github.com/Blacksujit/ML-Projects.git

2. Navigate to the specific project folder:

   cd /path/to/notebook

3. Follow the installation instructions to set up dependencies.

4. Run the project scripts.

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Installation:

To install the required dependencies, run the following command:

pip install -r requirements.txt

Make sure Python (3.x) and pip are installed on your system.

Contributing

Contributions are always welcome! Feel free to fork this repository and submit pull requests for:

• Adding new projects
• Improving existing code
• Fixing issues

To contribute:

1. Fork the repository.

2. Create a new branch for your feature:

   git checkout -b feature-branch

3. Commit your changes and push to your fork.

4. Submit a pull request.

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Contact

If you have any questions, suggestions, or feedback, feel free to reach out:

• GitHub: Blacksujit
• Email: [email protected]

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Thank you for visiting the repository! 😊

Star this repository if you find it useful! ⭐