v1.0

🚀 Release v1.0 — Full MLOps Automation

This release marks the first stable version of our pipeline with end-to-end automation for a regression task on the Ames Housing dataset. Key features include:

✅ Key Highlights

• ✅ MLflow integration for experiment tracking and reproducible runs
• ⚙️ Hydra-powered configuration management for clean and flexible parameter control
• 📊 Weights & Biases (W&B) logging for model metrics, artifacts, plots, and traceability
• 📁 Modular architecture with support for preprocessing, training, evaluation, and inference
• 📦 Full compatibility with mlflow run . -P steps="..." commands
• 🧪 Metrics evaluation using custom regression metrics
• 🧠 Feature selection and preprocessing pipeline tracking

This version is a robust foundation for reproducible and scalable machine learning pipelines.