Time Series Forecasting — ARIMA, SARIMA, Prophet, LSTM, Transformers for Time Series

ARIMA, Prophet, LSTM, Transformers

Author: AI Learning Club Team · Difficulty: Intermediate · Duration: 2 hr 10 min · Modules: 25

Modules

1. Introduction to Time Series Data (5 min)
2. Exploratory Data Analysis for Time Series (5 min)
3. Stationarity and Differencing (5 min)
4. ARIMA Models (5 min)
5. Seasonal ARIMA (SARIMA) Models (5 min)
6. Model Diagnostics and Evaluation (5 min)
7. Feature Engineering for Time Series (5 min)
8. Introduction to Prophet (5 min)
9. Advanced Techniques in Prophet (5 min)
10. Time Series Forecasting with LSTM (5 min)
11. Building LSTM Models for Time Series (5 min)
12. Transformers for Time Series Forecasting (5 min)
13. Advanced Transformers Techniques (5 min)
14. Ensemble Methods for Time Series (5 min)
15. Case Studies in Time Series Forecasting (5 min)
16. Time Series Forecasting in Practice (5 min)
17. Handling Missing Data in Time Series (5 min)
18. Multivariate Time Series Forecasting (5 min)
19. Time Series Anomaly Detection (5 min)
20. Forecasting with External Variables (5 min)
21. Time Series Forecasting in Business (5 min)
22. Deploying Time Series Models (5 min)
23. Ethical Considerations in Forecasting (5 min)
24. Future Trends in Time Series Forecasting (5 min)
25. Resources & References (2 min)

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