Machine learning in software engineering enhances development processes by automating tasks like code generation, bug detection, and testing. It improves efficiency, predicts software defects, and optimizes performance, transforming how software is built and maintained.

Machine learning (ML) is revolutionizing software engineering by automating and optimizing various aspects of the development lifecycle. It enables intelligent code completion, bug detection, and automated testing, reducing manual effort and improving code quality. ML models can predict software defects, optimize performance, and enhance security by identifying vulnerabilities in code. Additionally, it aids in project management by forecasting timelines and resource requirements, ensuring smoother workflows. By analyzing historical data, ML helps developers make data-driven decisions, accelerating development cycles and improving software reliability. From automating repetitive tasks to enabling predictive maintenance, machine learning is transforming how software is designed, built, and maintained, driving efficiency and innovation in the field.