Description
Regression: Create a linear regression model in python using any dataset of your choice. For this model you can also create your own data. Find the best fit linein the data and calculate SSE (sum of square error) or MSE (Mean square error) , Y intercept, and Slope for the relationship in data. Explain your findings and understanding of these terms in detail in the report.
Exercise Requirements:
1)Successfully executing the code with linear regression model and calculating following: a.SSE or MSEb.Y intercept c.Slope
2)Detail explanation of each in report
3)overallcode quality
4)WikiReport quality, video explanation
