Projects

KO | EN

gitlite — search

#python #hacktoberfest #react #llm #go #android #rust #deep-learning #docker #java #awesome #awesome-list #ios #open-source

(★ 113)

Final Project materials and description.

Projects Latest Version Download

Download Latest Version (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Projects

Materials for the Project in COGS108.

## Project Documentation

* [Project Guidelines](https://github.com/COGS108/Projects/blob/master/FinalProject_Guidelines.md)
* [Team Policies](https://github.com/COGS108/Projects/blob/master/COGS108_TeamPolicies.md)

## Project Templates

Templates have been provided in your group's project repo.

* Proposal: ProjectProposal_groupXXX-Fa22.ipynb
* Checkpoint #1: DataCheckpoint_groupXXX-Fa22.ipynb
* Checkpoint #2: EDACheckpoint_groupXXX-Fa22.ipynb
* Final Report: FinalProject_groupXXX-Fa22.ipynb

## Final Project Checklist

Students often ask for a rubric. You can use this checklist to help guide your thinking on the final project. If you check off all the boxes below, you should be in good shape to get a perfect score on your final project.

### Overview, Question & Background

**Overview**:
- [ ] Write a clear summary of what you did
- [ ] Briefly describe the results of your project 
- [ ] Limit overview to 3-4 sentences

**Research Question**:
- [ ] Include a specific, clear data science question
- [ ] Make sure what you're measuring (variables) to answer the question is clear

**Background & Prior Work**:
- [ ] Include a general introduction to your topic
- [ ] Include explanation of what work has been done previously
- [ ] Include citations or links to previous work

**Hypothesis**:
- [ ] Include your team's hypothesis
- [ ] Ensure that this hypothesis is clear to readers
- [ ] Explain why you think this will be the outcome (what was your thinking?)

### Dataset(s):
- [ ] Include an explanation of dataset(s) used (i.e. features/variables included, number of observations, information in dataset)
- [ ] Source included (if outside dataset(s) being used)

### Data Analysis:

**Data Cleaning & Pre-processing**
- [ ] Perform Data Cleaning and explain steps taken OR include an explanation as to why data cleaning was unnecessary (how did you determine your dataset was ready to go?)
- [ ] Dataset actually clean and usable after data wrangling steps carried out

**Data Visualization**:
- [ ] Include at least three visualizations
- [ ] Clearly label all axes on plots
- [ ] Type of all plots appropriate given data displayed
- [ ] Interpretation of each visualization included in the text

**Data Analysis & Results**:
- [ ] EDA carried out with explanations of what was done and interpretations of output included
- [ ] Appropriate analysis performed 
- [ ] Output of analysis interpreted and interpretation included in notebook

### Privacy/Ethics Considerations:
- [ ] Thoughtful discussion of ethical concerns included
- [ ] Ethical concerns consider the whole data science process (question asked, data collected, data being used, the bias in data, analysis, post-analysis, etc.)
- [ ] How your group handled bias/ethical concerns clearly described

### Conclusion & Discussion:
- [ ] Clear conclusion (answer to the question being asked) and discussion of results
- [ ] Limitations of analysis discussed
- [ ] Does not ramble on beyond providing necessary information

### Video:
- [ ] Question asked is clear to listeners
- [ ] Effective visualizations presented
- [ ] Clear explanations throughout
- [ ] Take home message clear
- [ ] Within 3-5 min time limit

### Final Checks:
- [ ] Edit all text for clarity
- [ ] Remove all instructions
- [ ] Be sure text included throughout to guide reader
- [ ] Check to make sure all text and images are visible
- [ ] Names included
- [ ] Renamed file : `FinalProject_groupXXX-Fa22.ipynb`, where 'XXX' is replaced by your group's group number

### After the course is done:
- If you checked YES to make project public: the final project notebook (and only that!) will be placed in a repo with the rest of this quarters public reports. This helps future students by providing examples!
- Your projct repo will remain available to you in the near future. We cannot guarentee that will always be the case. That repo will never be public.
- If you would like your own copy of the entire repo you should follow these instructions: https://docs.github.com/en/repositories/creating-and-managing-repositories/duplicating-a-repository Once you have done that it is yours forever. You will also be able to control access to the mirror (make it public or private as you would prefer)

---
## License

The content of this project itself is licensed under the [Creative Commons Attribution 3.0 Unported license](https://creativecommons.org/licenses/by/3.0/).

Projects

Projects Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Projects

Projects Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Download README