predict

🧠 ML / AI Model Demo

Short description of the project. Example: A machine learning model that predicts house prices using regression.

📌 Features

Train and evaluate ML model

Data preprocessing pipeline

Inference / prediction script

Simple demo example

🧾 Project Structure ml-ai-demo/ │ ├── data/ # Dataset or sample data ├── models/ # Saved trained models ├── notebooks/ # Jupyter notebooks for experiments ├── src/ │ ├── train.py # Training script │ ├── predict.py # Inference script │ └── utils.py # Helper functions │ ├── requirements.txt └── README.md ⚙️ Installation

Clone the repository:

git clone https://github.com/username/ml-ai-demo.git cd ml-ai-demo

Install dependencies:

pip install -r requirements.txt 🚀 Training the Model python src/train.py

This will:

Load dataset

Train the model

Save it in models/

🔮 Run Prediction python src/predict.py –input sample_data.csv

Example output:

Prediction: 245000 📊 Example Results Metric Score Accuracy 92% F1 Score 0.89 🧪 Example Notebook

You can explore the training process in:

notebooks/model_demo.ipynb 📦 Requirements

Example:

python >= 3.9 numpy pandas scikit-learn torch 📝 Future Improvements

Add API for predictions

Deploy model with FastAPI

Improve dataset size

👤 Author

Your Name: Nandini Sharma GitHub: https://github.com/NandiniSharma5083

📜 License

MIT License

💡 Tip for ML repos: also include:

model architecture diagram

dataset source

example predictions

demo GIF