Practical Data Science using Python - Linear Regression - Training and Cost Function

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Information Technology (IT), Architecture, Mathematics
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University
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Hard
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4 questions
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1.
OPEN ENDED QUESTION
3 mins • 1 pt
Discuss the importance of preprocessing data before applying linear regression.
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2.
OPEN ENDED QUESTION
3 mins • 1 pt
Explain the concept of error minimization in linear regression.
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3.
OPEN ENDED QUESTION
3 mins • 1 pt
What does the R-squared value indicate in a linear regression model?
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4.
OPEN ENDED QUESTION
3 mins • 1 pt
What are residuals in the context of linear regression, and how are they calculated?
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