Modern Time Series Forecasting with Python - B22389_06 (for True Epub) by Unknown

Author:Unknown
Language: eng
Format: epub
Tags: deep learning time series; arima; stochastic; conformal prediction; demand forecasting; microeconomics; forecasting principles and practice
Publisher: Packt Publishing
Published: 2024-09-26T00:00:00+00:00

Summary

In this chapter, we learned about the key components of a time series and familiarized ourselves with terms such as trend, seasonality, and so on. We also reviewed a few time series-specific visualization techniques that will come in handy during EDA. Then, we learned about techniques that let you decompose a time series into its components and saw techniques for detecting outliers in the data. Finally, we learned how to treat the identified outliers. Now, you are all set to start forecasting the time series, which we will start in the next chapter.

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