automatic time series forecasting

Automatic time series forecasting uses computer algorithms to analyze historical data and predict future values without requiring extensive manual input. It identifies patterns such as trends, seasonal fluctuations, and irregularities in the data, then combines these insights to generate forecasts. This process helps businesses and analysts make informed decisions quickly and efficiently, reducing the need for specialized expertise. Essentially, automated forecasting systems streamline the process of predicting future data points by learning from past data and continuously improving their accuracy over time.