June 11, 2024, 10:19 a.m. | Mursal Furqan Kumbhar

DEV Community dev.to

Advanced Time-Series: Types, Methods, Applications and Top 20 Python Libraries 📈


Advanced time series forecasting involves using machine learning, and deep learning techniques to predict future values of time-dependent data, accounting for complex patterns and seasonality, trends.


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📈 Time series Types:


✶ Univariate

✶ Multivariate

✶ Stationary

✶ Non-Stationary

✶ Seasonal

✶ Non-Seasonal

✶ Irregular

✶ Regular

✶ Additive

✶ Multiplicative

✶ Periodic

✶ Non-Periodic


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⌛️ Here are several advanced time series forecasting methods:


› LSTM (Long Short-Term …

accounting advanced applications data datascience deep learning deep learning techniques forecasting future libraries machine machine learning machinelearning multivariate patterns programming python seasonality series time series time series forecasting trends types values

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