A Practical Approach to Timeseries Forecasting Using Python
 - Time Series Parameters

A Practical Approach to Timeseries Forecasting Using Python - Time Series Parameters

Assessment

Interactive Video

Computers

9th - 10th Grade

Hard

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The video tutorial covers four key parameters: correlation, MAP, MAE, and RMSE. It explains how to calculate correlation between data columns using pandas, and how to compute MAP and MAE using the sklearn library. The tutorial also demonstrates the calculation of RMSE using Python's math functions. The module concludes with a summary and a preview of upcoming topics, including machine learning applications in time series analysis.

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OPEN ENDED QUESTION

3 mins • 1 pt

What new insight or understanding did you gain from this video?

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