👟 jordan-predictor-pro

Simple, reproducible Machine Learning pipeline to validate, clean, train, and predict sneaker prices from stock values.

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🗂️ Project structure

• data/ 📁: raw and cleaned CSV data (tracked with DVC)
• src/ 🧠: Python scripts for generation, validation, cleaning, training, and prediction
• notebooks/ 📓: optional exploration notebooks
• tests/ 🧪: test placeholders
• dvc.yaml 🔁: pipeline definition

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🚀 Quick Start

1. Install dependencies:

   pip install -r requirements.txt

2. Generate data and train model:

   python src/generate_raw_data.py
   python src/clean_data.py
   python src/train.py

   Or run the full pipeline:

   dvc repro

3. Use the API or CLI for predictions 🔮 (see below)

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Pipeline (DVC)

Run full pipeline:

dvc repro

Run step-by-step:

python src/validate_data.py
python src/clean_data.py
python src/train.py

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🧪 Generate synthetic raw data

python src/generate_raw_data.py

CLI

python src/predict.py --stock 20

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API (FastAPI) 🌐

⚠️ Important: Train the model first (see Quick Start above)!

Start the API server:

uvicorn src.api:app --reload

Open your browser at http://127.0.0.1:8000/docs for interactive Swagger UI.

Endpoints:

• GET / - Welcome message
• GET /health - Check if model is loaded
• GET /predict?stock=<value> - Get price prediction

Example requests:

# Check health
curl "http://127.0.0.1:8000/health"

# Get prediction
curl "http://127.0.0.1:8000/predict?stock=20"