Path: blob/master/final_project/04-notebook-rough-draft/final-project-4-rubric.md
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RUBRIC
Final Project - Part 4 | Data Science
Your project will be assessed using the following standards, as defined by the data science workflow:
Refine & Build
Acceptable performance for this standard is based on how well you've applied specific learning goals within your deliverable. To review the full list of data science standards, see the course syllabus.
REFINE & BUILD
Meets Expectations: Did you: Document and transform your data? Apply descriptive and inferential statistics? Identify trends and outliers? Application of these learning goals will be assessed using the requirements below:
Performance Evaluation
Mark boxes with an 'X'
| Requirements | Incomplete (0) | Does Not Meet Expectations (1) | Meets Expectations (2) | Exceeds Expectations (3) |
|---|---|---|---|---|
| Create iPython Notebook with code, visualizations, and markdown | ||||
| Summarize your exploratory data analysis | ||||
| Frame source code so it enhances your explanations | ||||
| Explain your choice of validation and prediction metrics. | ||||
| Include a separate python module with helper functions | ||||
| Visualize relationships between Y and two strongest variables | ||||
| Identify areas where new data could help improve the model |
Notes: For this assignment, you will also need to review your data set and project with an EIR during office hours.
Score:
Based on the requirements, you can earn a maximum of 21 points on this project.
Your total score is: #
PROGRESS REPORT
Student Check-in:
| HIGHLIGHTS | GROWTH OPPORTUNITIES | DEVELOPMENT PLAN |
|---|---|---|