Automated Machine Learning

Automated Machine Learning (AutoML) is the process of using software to automatically select, train, and fine-tune machine learning models without extensive human intervention. It simplifies the complex tasks typically involved in machine learning, such as data preparation, feature selection, and model evaluation. By automating these steps, AutoML makes it easier for non-experts to apply machine learning techniques to solve real-world problems, enabling faster results and expanding access to powerful data-driven insights. Essentially, it democratizes the use of machine learning by making it more user-friendly and efficient.