PDC4S:\IT\DATA SCIENCE AND MACHINE LEARNING\[365 Data Science] Programming for Data Science\20. Time Series Analysis in Python | ||
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 1. Introduction | ||
| 10. The Autoregressive Integrated Moving Average (ARIMA) Model | ||
| 11. The ARCH Model | ||
| 12. The GARCH Model | ||
| 13. Auto ARIMA | ||
| 14. Forecasting | ||
| 15. Business Case | ||
| 2. Setting up the working environment | ||
| 3. Introduction to Time Series in Python | ||
| 4. Creating a Time Series Object in Python | ||
| 5. Working with Time Series in Python | ||
| 6. Picking the Correct Model | ||
| 7. The Autoregressive (AR) Model | ||
| 8. The Moving Average (MA) Model | ||
| 9. The Autoregressive Moving Average (ARMA) Model | ||