Automated Machine Learning (AutoML) is a process that automates the end-to-end tasks of applying machine learning to real-world problems. It simplifies the workflow by automatically selecting algorithms, tuning parameters, and preprocessing data, making it accessible to users without extensive expertise in data science. By streamlining these tasks, AutoML allows businesses and researchers to focus on interpreting results and making decisions rather than getting bogged down in technical details. This technology can significantly speed up the development of machine learning models, enabling faster insights and more efficient use of resources.