Welcome to linear regression with Codecademy!
Curriculum Developers Sophie and Alex will continue to walk us through our Linear Regression in Python Course. Check out the full course here: https://j.mp/33HACXe
Have questions about this livestream? Join us for office hours on Thursday, June 24 at 11:00 AM on our Discord server: https://bit.ly/3px5QKy
More details:
In our sixth session, we'll learn about data pre-processing that is useful prior to fitting a linear regression model. These kinds of transformations are potentially helpful when the assumptions of linear regression are otherwise violated. Pre-processing can also make the regression output more interpretable and therefore easier to communicate to a non-technical audience.
The code used in this video can be found here: https://github.com/Codecademy/Linear-Regression-Live-Series
- - - - -
Join the millions learning to code with Codecademy.
Learn to code: https://j.mp/3tIq04H
Check out our full course catalog: https://j.mp/3yaKRkz
Curriculum Developers Sophie and Alex will continue to walk us through our Linear Regression in Python Course. Check out the full course here: https://j.mp/33HACXe
Have questions about this livestream? Join us for office hours on Thursday, June 24 at 11:00 AM on our Discord server: https://bit.ly/3px5QKy
More details:
In our sixth session, we'll learn about data pre-processing that is useful prior to fitting a linear regression model. These kinds of transformations are potentially helpful when the assumptions of linear regression are otherwise violated. Pre-processing can also make the regression output more interpretable and therefore easier to communicate to a non-technical audience.
The code used in this video can be found here: https://github.com/Codecademy/Linear-Regression-Live-Series
- - - - -
Join the millions learning to code with Codecademy.
Learn to code: https://j.mp/3tIq04H
Check out our full course catalog: https://j.mp/3yaKRkz
- Category
- Codecademy
- Tags
- linear regression, python, machine learning

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