AutoML

AutoML, or Automated Machine Learning, refers to a suite of processes and technologies designed to simplify and streamline the development of machine learning models. It aims to make machine learning more accessible by automating tasks traditionally requiring significant expertise, such as data preprocessing, feature selection, and model selection. By leveraging AutoML, organizations can accelerate model development, reduce the need for specialized knowledge, and enhance the efficiency of their machine learning workflows. This technology also helps democratize machine learning, enabling more users to build and deploy models effectively without deep technical skills.