Time Series

Time Series Machine Learning focuses on analyzing sequential data collected over regular intervals of time.
It uses historical observations to forecast future outcomes and identify hidden temporal patterns.
Popular models include ARIMA, SARIMA, Prophet, LSTM, and Transformer-based forecasting models.
These techniques are widely used in finance, healthcare, IoT, weather forecasting, and business analytics.
Time series models help organizations make better decisions by predicting future trends and anomalies.
Modern AI systems combine Machine Learning and Deep Learning techniques to improve forecasting accuracy and scalability.