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Linear and polynomial regression in Python.

This brief tutorial demonstrates how to use Numpy and SciPy functions in Python to regress linear or polynomial functions that minimize the least squares difference between measured and predicted values.

Bibliographic Details
Format: Video
Language:English
Language Notes:In English.
Published: [Place of publication not identified] : APMonitor.com, 2021.
Series:Academic Video Online
Subjects:
Python (Computer program language)
Regression analysis > Data processing.
Python (Langage de programmation)
Analyse de régression > Informatique.
Regression analysis > Data processing
Educational films
Instructional films
Educational films.
Instructional films.
Films éducatifs.
Films de formation.
Online Access:Connect to this streaming video (Alexander Street Press)
Description
Summary:This brief tutorial demonstrates how to use Numpy and SciPy functions in Python to regress linear or polynomial functions that minimize the least squares difference between measured and predicted values.
Item Description:Title from resource description page (viewed March 28, 2022).
Physical Description:1 online resource (16 minutes)
Playing Time:00:15:20