Homoscedasticity: The variance of residuals should be equal.Linearity: The relationship between independent variables and the mean of the dependent variable is linear.There are four assumptions associated with a linear regression model: In regression, we try to calculate the best fit line, which describes the relationship between the predictors and predictive/dependent variables. It assumes that there is a linear relationship between the dependent variable and the predictor(s). Linear Regression is the basic form of regression analysis. Building the model on Train Data and Predict on Test Data.Which Regression Model is the best fit for the data?.Advanced Linear Regression with statsmodels.Polynomial Regression With scikit-learn.Multiple Linear Regression With scikit-learn.Simple Linear Regression With scikit-learn.Implementing Linear Regression in Python.Isn’t Linear Regression from Statistics?.Master of Business Administration Degree Program.Design Thinking : From Insights to Viability.NUS Business School : Digital Transformation.PGP in in Product Management and Analytics.PGP in Software Development and Engineering.PG Diploma in Artificial Intelligence – IIIT-Delhi.Advanced Certification in Software Engineering.PGP in in Software Engineering for Data Science.Advanced Certificate Program in Full Stack Software Development.

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