AutoAPE-challenge2 and AutoAPE-challenge3

These are ecosystem siblings representing successive iterations of the same annual Kaggle competition series, where challenge3 (2022) builds upon and supersedes the previous year's challenge2 (2021) framework.

AutoAPE-challenge2
39
Emerging
AutoAPE-challenge3
38
Emerging
Maintenance 0/25
Adoption 8/25
Maturity 8/25
Community 23/25
Maintenance 0/25
Adoption 8/25
Maturity 8/25
Community 22/25
Stars: 51
Forks: 66
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: —
Stars: 56
Forks: 63
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: —
No License Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

About AutoAPE-challenge2

seculayer/AutoAPE-challenge2

Kaggle 2차년도(2021)

This is a framework for organizing and sharing the results and code from your participation in Kaggle or Dacon AI competitions. It helps you document your competition entries, including your scores, ranks, team members, and the technical approaches used. The output is a structured, easy-to-understand record of your contributions, ideal for individuals or teams participating in data science challenges.

data-science-competitions machine-learning-engineering project-documentation team-collaboration AI-challenges

About AutoAPE-challenge3

seculayer/AutoAPE-challenge3

Kaggle 3차년도(2022)

This is a repository to collect and organize solutions and results from AI competitions like Kaggle and Dacon. Participants submit their competition code, along with a metadata file detailing their score, rank, and team information, and a README summarizing their approach. It's intended for individuals or teams who regularly participate in data science and machine learning challenges and want to keep a structured record of their past work.

AI Competition Data Science Challenges Machine Learning Projects Team Collaboration Solution Archiving

Scores updated daily from GitHub, PyPI, and npm data. How scores work