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Good work! This submission fully meets the assignment requirements
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PULL REQUEST TITLE: UofT-DSI | Production - Assignment 2
What changes are you trying to make? (e.g. Adding or removing code, refactoring existing code, adding reports)
Add code to load data from a csv file into a data frame.
Add code to create features data frame and target data.
Use column transformers function for linear and non-linear transformation and one-hot encoding function to preprocess data.
Add code to create 4 different model pipelines and use baseline and advance regressor to perform a prediction.
Add code to perform GridSearch and parameters grid with the 4 pipelines.
Add code to evaluate the best performance among the 4 pipelines.
Export pipeline into a pickle file.
Add code to use SHAP values to explain the features in the best-performing model.
What did you learn from the changes you have made?
How to use column transformers function and one-hot encoding.
How to use different types of regressors to perform a prediction.
How to SHAP values to determine the impact of features on the model performance.
Was there another approach you were thinking about making? If so, what approach(es) were you thinking of?
N/A
Were there any challenges? If so, what issue(s) did you face? How did you overcome it?
Using one-hot encoding for categorical features, using non-linear functions, and evaluating the model performance for multiple models.
I reviewed the slides to understand the concepts behind the new functions and reviewed the the live coding files to see how it could be applied to the questions.
How were these changes tested?
The changes were tested by running each code to see if expected values were returned.
A reference to a related issue in your repository (if applicable)
N/A
Checklist