gueei / date-a-scientist Goto Github PK

Rubric Score

Criteria 1: Valid Python Code

• Score Level: 4 (Exceeds Expectations)
• Comment(s): Code runs without errors. Excellent use of functions, loops, custom module imports, and advanced matplotlib/pandas functionality.

Criteria 2: Exploration of Data

• Score Level: 4 (Exceeds Expectations)
• Comment(s): Data thoroughly explored and features chosen to answer questions follow logically from the exploration. Careful attention was paid to outliers and pair plots are used to visualize relationships between features.

Criteria 3: Machine Learning Techniques Used Correctly

• Score Level: 4 (Exceeds Expectations)
• Comment(s): Algorithms are used correctly and the correct conclusions are drawn from the results.

Criteria 4: Report: Are conclusions clear and supported by data?

• Score Level: 3 (Meets Expectations)
• Comment(s): Report is clean, although a little sparse. Conclusions are supported by evidence and comparisons between models are succinct. Report ends abruptly and could have used an introduction to guide the reader.

Criteria 5: Code Formatting

• _Score Level:_3 (Meets Expectations)
• Comment(s): Code is clearly formatted but lacks comments that would help a reader follow along.

Overall Score: 18/20

Great job! Overall, you hit all the requirements of the project and went out of your way to include a number of visualizations that highlight the amount of thought and research that went into the project. Very nicely done.