From the course: Practical Python for Time Series Analysis

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Feature engineering fundamentals

Feature engineering fundamentals - Python Tutorial

From the course: Practical Python for Time Series Analysis

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Feature engineering fundamentals

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- [Instructor] Feature engineering on time series data. A feature is a new column on the dataset that you use on the linear regression. In this case, you observe that the dataset we're working with contains the historical information from the year 1948s, and it's the raw data. By the time that we try to develop the linear regression, it's a total mess because there are many periods that should have been taken into account on this dataset. If we recall the previous chapter, we learned how to develop the linear relation with an already calculated categorical column where the relationship, if we didn't have the categorical column, was very poor, and after that it improved significantly. Now that you have learned the differences between applying the categorical column or not, you're ready to work with the raw historical data that only contains the information of the indicators. And the techniques that you will learn are…

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