Assess your Course 6 end-of-course project :The Nuts and Bolts of Machine Learning (Google Advanced Data Analytics Professional Certificate) Answers 2025

1. Applicable packages and libraries were imported to the code notebook.
✔ Yes
❌ No

2. Categorical variables were encoded as binary variables.
✔ Yes
❌ No

3. A target variable was assigned.
✔ Yes
❌ No

4. An evaluation metric was chosen.
✔ Yes
❌ No

5. The data was split into training and testing sets.
✔ Yes
❌ No

6. The following steps were performed for the random forest model:
✔ Performed a GridSearch to tune hyperparameters
✔ Captured precision, recall, F1 score, and accuracy metrics
✔ Obtained validation scores of best model

7. The following steps were performed for the XGBoost model:
✔ Performed a GridSearch to tune hyperparameters
✔ Captured precision, recall, F1 score, and accuracy metrics
✔ Obtained validation scores of best model

8. The random forest model was compared to the XGBoost model.
✔ Yes
❌ No

9. A confusion matrix was plotted.
✔ Yes
❌ No

10. The top 10 most important features of the final model were inspected.
✔ Yes
❌ No

11. All questions in the code notebook were answered.
✔ Yes
❌ No

12. All questions in the PACE strategy document were answered.
✔ Yes
❌ No

13. The executive summary clearly articulated the challenges presented in this data project.
✔ Yes
❌ No

14. The executive summary identified the outcome of your work.
✔ Yes
❌ No

15. The executive summary included recommendations for future work/next steps.
✔ Yes
❌ No

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