UofT-DSI | <LCR> - Assignment 2

[hashimi07]

What changes are you trying to make? (e.g. Adding or removing code, refactoring existing code, adding reports)

Completed Assignment 2 for the Linear Regression module. Added code and answers to assignment_2.ipynb, including data inspection, visualization, multivariable linear regression modeling, and model evaluation.

What did you learn from the changes you have made?

I practiced using pandas, scikit-learn, and matplotlib to analyze real-world data, fit and interpret a linear regression model, and evaluate its performance.

Was there another approach you were thinking about making? If so, what approach(es) were you thinking of?

For this assignment, I followed the standard workflow as outlined in the course. Otherwise I am not to sure of other methods to use for now.

Were there any challenges? If so, what issue(s) did you face? How did you overcome it?

I encountered some minor package/environment setup issues (e.g., missing libraries and kernel restarts), but resolved them using pip install and reviewing error messages.

How were these changes tested?

All lines of code were executed and had the green check mark without no errors.

A reference to a related issue in your repository (if applicable)

Checklist

• [Yes ] I can confirm that my changes are working as intended

[KasraVakiloroayaei]

A2: Incomplete

Good work, however there is a minor edit that needs to be done in the last question. When calculating the RMSPE, it may be more helpful to use the mean_squared_error() function with the correct arguments then take the square root of all of that, using np.sqrt(). I believe after making these changes you will have the correct RMSPE value