A Practical Approach to Timeseries Forecasting Using Python
 - Autoregression

A Practical Approach to Timeseries Forecasting Using Python - Autoregression

Assessment

Interactive Video

Computers

10th - 12th Grade

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

The video tutorial introduces the concept of auto regression, explaining how it uses past data to predict future values. It details the role of the parameter P in determining time lags and provides an example using a milk distribution company. The tutorial also covers the implementation of auto regression in Python, highlighting necessary modules like TQDM and Evaluate.

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3 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the role of the coefficient factor in determining the impact of previous time spots?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

How can the order of an Arkansas model be determined based on threshold values?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What steps are necessary to implement auto regression in Python?

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