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oliver-evans-digital-portfolio

A digital portfolio for me!

https://github.com/cholliedawg/oliver-evans-digital-portfolio

Science Score: 31.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
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    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
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    DOI references
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    Academic links in README
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    Academic email domains
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    Institutional organization owner
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    JOSS paper metadata
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    Scientific vocabulary similarity
    Unable to calculate vocabulary similarity
Last synced: 10 months ago · JSON representation ·

Repository

A digital portfolio for me!

Basic Info
  • Host: GitHub
  • Owner: ChollieDawg
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 15.5 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Citation

Owner

  • Name: Chollie
  • Login: ChollieDawg
  • Kind: user
  • Location: Vancouver, BC

I enjoy data, analytics, python, stock market, side hustles and video games.

Citation (citations.md) 

# Acknowledgments

I would like to extend my gratitude to:

- **Mentors and Colleagues**: Special thanks to all my peers and colleagues for their guidance and support in my journey.
- **Resources and Tools**: Many thanks to the [Jupyter Book](https://jupyterbook.org/) community for providing an incredible platform, and to open-source contributors for libraries like Pandas, Matplotlib, and scikit-learn, which made this project possible.
- **Family and Friends**: Heartfelt thanks to my family and friends for their support and encouragement and allowing me to provide them random cheese and planet/star facts sporadically.

## References

1. Jupyter Book Documentation. Available at: [https://jupyterbook.org/](https://jupyterbook.org/)
2. McKinney, W. (2012). *Python for Data Analysis*. O'Reilly Media.
3. Sweigart, A. (2015). *Automate the Boring Stuff with Python*. No Starch Press.
4. Guttag, J. (2013). *Introduction to Computational Programming using Python*. MIT Press.
5. scikit-learn: Machine Learning in Python. Available at: [https://scikit-learn.org/](https://scikit-learn.org/)
6. Wikipedia, The Free Encyclopedia. Available at: [https://www.wikipedia.org/](https://www.wikipedia.org/)

For a comprehensive list of resources, please refer to each section within the project.

GitHub Events

Total
  • Push event: 2
  • Create event: 2
Last Year
  • Push event: 2
  • Create event: 2

Dependencies

requirements.txt pypi
  • altair *
  • jupyter-book *
  • matplotlib *
  • numpy *