Machine Learning Project Repository

📖 Project Overview

This repository contains a collection of machine learning projects and assignments covering various algorithms and techniques. The projects include implementations of K-Nearest Neighbors (KNN), Regression Models, Support Vector Machines (SVM), and Neural Networks (NN), along with datasets for practice and experimentation.

🛠️ Technology Used

• Programming Language: Python
• Libraries:
  • Scikit-learn (for ML models)
  • Pandas (for data manipulation)
  • NumPy (for numerical operations)
  • Matplotlib/Seaborn (for visualization)
• Tools:
  • Jupyter Notebook (for interactive coding)
  • Git (for version control)

How to Use and Run

1. Clone the Repository:

   git clone https://github.com/MidoHossam14/MachineLearningAlgorithms.git
   cd FULL-PROJECT

2. Install Dependencies:

   Ensure you have Python installed (recommended: Python 3.9). Install the required libraries using:

   pip install -r requirements.txt

3. Run Jupyter Notebooks:

   Navigate to the notebooks folder and launch Jupyter:

   jupyter notebook
   

• Open the desired notebook (e.g., KNN-Model.ipynb) and execute the cells to run the code.

4. Datasets:

   The data folder contains datasets (e.g., Iris.csv, Titanic.csv). Ensure the notebook paths to these datasets are correctly set.

📂 Repository Structure

📦Full-Project
 ┣ 📂data
 ┃ ┣ 📜CarPricePrediction.csv
 ┃ ┣ 📜Iris.csv
 ┃ ┗ 📜Titanic.csv
 ┣ 📂notebooks
 ┃ ┣ 📂KNN-CrossValidation
 ┃ ┃ ┣ 📜KNN-Model.ipynb
 ┃ ┃ ┗ 📜README.md
 ┃ ┣ 📂RegressionModels
 ┃ ┃ ┣ 📜README.md
 ┃ ┃ ┗ 📜RegressionModels.ipynb
 ┃ ┗ 📂SVM-NN Models
 ┃ ┃ ┣ 📜README.md
 ┃ ┃ ┗ 📜SVM-NN-Models.ipynb
 ┣ 📜README.md
 ┗ 📜LICENSE
 ┗ 📜requirements.txt

🛠️ Contributing

Contributions are welcome! To contribute:

1. Fork the repository.

2. Create a new branch for your feature/fix:

   git checkout -b feature-name
   

3. Commit your changes and push to the branch.

4. Open a Pull Request with a clear description of your changes.

🛡️ License

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

☕ Stay Connected

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