AutoML Time Series

Is a machine learning approach that automates the process of building, selecting, and tuning models for time-based data. It enables users to perform tasks like forecasting, anomaly detection, and trend analysis without needing deep expertise in data science.

By handling tasks such as feature engineering, model selection, and hyperparameter optimization automatically, AutoML for time series accelerates insights and improves accuracy across industries like finance, retail, manufacturing, and energy.