# Final Project Rubric

#### Points Necessary by Team Size

For an individual worker (team of 1), a 100% grade requires 25 earned points.
For a team of two, a 100% grade requires 35 points.

Team Size |
Pts for 100% |
… for 90% |
… for 80% |

1 |
25 |
22.5 |
20 |

2 |
35 |
31.5 |
28 |

#### Earning Points

##### Data Acquisition

Points |
Max |
Task |

**2** |
2 |
Acquire a dataset from the internet |

**1** |
3 |
For **each** dataset acquired and used beyond the first |

**2** |
2 |
Create a dataset yourself to work with other data you found online; e.g. a mapping of state abbreviations to state names. |

##### Data Wrangling

Points |
Max |
Task |

**4** |
4 |
Use at least one join |

**3** |
3 |
Melt and/or reshape your data |

##### Modeling

Points |
Max |
Task |

**2** |
6 |
For each linear model trained and used in your project |

**3** |
9 |
For each nonlinear model trained and used in your project |

**0.5** |
3 |
For each statistical metric (mean, median, mode) included in your final deliverable(s) |

**1** |
6 |
For **each** plot included in your final deliverable(s) |

Points |
Max |
Task |

**6** |
6 |
Version control your code using a public GitHub repository (easy points – this makes it infinitely easier for me to grade). If you have two team members, **both people must have a commit recorded in the Git history** to get these points. |

**0.5** |
3 |
For each additional Git commit beyond the first. |

**Up to 5** |
5 |
Points at the instructor’s discretion for particularly impressive projects |

##### Stretch Goals (topics not included in the course lectures)

Points |
Task |

**4** |
Pull data from a web-based API (I recommend the Requests library) |

**5** |
Scrape data from a website using Beautiful Soup and/or Scrapy. |

**5** |
Create a web dashboard using Dash. |

**4** |
Correctly train and make predictions using a neural network (I recommend Keras). |