Machine Learning & AI Projects 🚀

A collection practical machine learning and AI projects showcasing different applications and technologies.

📁 Projects Overview

1. 🔢 Handwritten Digit Recognition

Tech Stack: Python, Scikit-learn, Matplotlib, NumPy

• Recognizes handwritten digits (0-9) using machine learning
• Built with scikit-learn's digit dataset
• Implements classification algorithms for digit prediction
• Interactive visualization of results

2. 🏠 Bengaluru Home Price Prediction

Tech Stack: Python, Pandas, Scikit-learn, Flask, Streamlit

• Predicts real estate prices in Bengaluru based on various features
• Uses regression algorithms for price estimation
• Features: location, size, Bhk, Bath
• Web interface for easy price predictions

3. 📧 Cold Email Generator

Tech Stack: Python, Streamlit, Groq API, ChromaDB, LangChain

• AI-powered cold email generation for job applications
• Web scrapes job postings and matches with portfolio
• Personalized email creation using LLM
• Vector database for intelligent content matching

4. 🫁 AI-Powered Pneumonia Detection System

Tech Stack: Python, TensorFlow, Keras, Streamlit, PIL

• Analyzes chest X-ray images to detect pneumonia using deep learning
• Uses Convolutional Neural Networks (CNN) for medical image classification
• Features: Image upload, AI diagnosis, confidence scoring, medical disclaimer
• Modern web interface with real-time processing and professional UI

🚀 Quick Start

1. Clone the repository

   git clone https://github.com/Rupayan2005/ML-Project.git

2. Navigate to any project

   cd Hand Written Digit Recognition
   # or
   cd Home_prediction
   # or
   cd cold email generator
   # or
   cd Pneumonia Detector

📊 Project Details

Project	Algorithm	Dataset	Interface
Digit Recognition	SVM/Random Forest	Scikit-learn Digits	Matplotlib/Jupyter
Price Prediction	Linear Regression	Real Estate Data	Web App
Email Generator	LLM (Groq)	Job Postings	Streamlit
Pneumonia Detector	Keras	Pneumonia Classifier	Streamlit

🛠️ Prerequisites

• Python 3.8+
• Required packages (see requirements.txt)
• API keys for Cold Email Generator (Groq)

📝 Usage

Each project folder contains:

• README.md - Project-specific documentation

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Open a Pull Request

🙏 Acknowledgments

• Scikit-learn for machine learning algorithms
• Streamlit for web interfaces
• Groq for LLM API
• TensorFlow for the machine learning framework

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