This article explains how to use dbt's defer feature to improve CI/CD pipeline efficiency by only rebuilding modified models instead of the entire project. It covers the setup process, benefits, and potential pitfalls of implementing defer in dbt workflows.

MLOps integrates machine learning with DevOps practices to streamline the model development lifecycle, focusing on automation, reproducibility, and performance monitoring. This blog details a practical project to build a House Price Predictor using Azure DevOps for CI/CD, covering setup, data processing, feature engineering, model training, and deployment to Azure Kubernetes Service.