Installation Guide¶
Detailed installation instructions for development and production environments.
System Requirements¶
| Component | Minimum | Recommended |
|---|---|---|
| Python | 3.11 | 3.12 |
| RAM | 4 GB | 8 GB |
| Disk | 10 GB | 20 GB |
| Docker | 20.10+ | Latest |
Installation Methods¶
Method 1: Docker (Recommended)¶
# Clone repository
git clone https://github.com/DuqueOM/ML-MLOps-Portfolio.git
cd ML-MLOps-Portfolio
# Start all services
docker compose -f docker-compose.demo.yml up -d --build
Method 2: Local Python¶
# Clone repository
git clone https://github.com/DuqueOM/ML-MLOps-Portfolio.git
cd ML-MLOps-Portfolio
# Create virtual environment
python -m venv .venv
source .venv/bin/activate
# Install project (example: BankChurn)
cd BankChurn-Predictor
pip install -e ".[dev]"
Method 3: Development Setup¶
See Development Setup for full developer environment configuration.
Verification¶
# Check Docker services
docker compose -f docker-compose.demo.yml ps
# Run integration tests
bash scripts/run_demo_tests.sh
Troubleshooting¶
See Troubleshooting Guide for common issues.
Last Updated: March 2026 — v3.5.3