An autoregressive model is a type of statistical model that predicts future values based on past values. It's commonly used in time series analysis, speech processing, and natural language processing to forecast trends, generate sequences, and model dependencies between data points over time. For example, it can predict future stock prices based on past prices or generate realistic-sounding speech based on previous speech segments.
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