🤖 Machine Learning Projects

A curated collection of end-to-end Machine Learning projects built using Python and scikit-learn. This repository demonstrates the complete ML workflow—from data preprocessing to model training, evaluation, visualization, and prediction.

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🔗 Live Demo:
https://predict-ui-dashboards.streamlit.app/

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📌 About This Repository

This repository serves as a learning lab and portfolio where I build and organize machine learning projects to strengthen practical skills in:

• Data preprocessing & feature engineering
• Model training and evaluation
• Visualization and reporting
• Saving and loading models
• Building modular and reusable ML pipelines

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🧠 Projects Included

Project	Description	Status
🎓 Student Pass/Fail Prediction	Predicts whether a student will pass or fail based on exam scores	✅ Completed
📊 Reading Score Prediction	Predicts student reading performance using exam data	✅ Completed
🚀 More projects coming soon	New ML experiments and models will be added	🔄 In Progress

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⚙️ Tech Stack

• Python 🐍
• Pandas & NumPy
• Scikit-learn
• Matplotlib
• Joblib

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🗂️ General Project Structure

Most projects follow a structure like this:

project-name/
│
├── data/           # Dataset files
├── src/            # Source code
├── models/         # Saved models
├── reports/        # Charts and evaluation outputs
├── requirements.txt
└── README.md

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▶️ How to Run a Project

1. Clone the repository

git clone https://github.com/Atharv-AC/machine-learning-projects.git

2. Navigate to a project folder

cd project-folder

3. Install dependencies

pip install -r requirements.txt

4. Run the project

python src/main.py

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📈 Goals of This Repository

This repository is part of my journey to:

• Strengthen machine learning fundamentals
• Build real-world style ML pipelines
• Improve project structure and documentation
• Prepare for data science and ML roles

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🚀 Future Improvements

Planned additions:

• More classification and regression projects
• Model comparison and hyperparameter tuning
• Streamlit dashboards
• Deployment using FastAPI

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👨‍💻 Author

Atharv Chandurkar

GitHub: https://github.com/Atharv-AC

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⭐ If you find this repository useful

Consider giving it a star—it helps and motivates me to build more projects!

💡Note: Each project includes its own detailed README with specific instructions, dataset information, and feature documentation.