In this video, we will complete the implementation that we had started in the previous video using Python. We are going to write the complete code for the regression model using Pure Python without using scikit-learn. We will plot the regression model, make predictions for unforeseen data, compute the RSS, Residual Standard Error in general and over an interval. Finally, we will evaluate the performance metrics of the model to compute the statistical power of prediction of our model using the values of RSS and TSS that we get to get the value for RSE and R_Squared.
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