rafaelgreca / e2e-mlops-project

The purpose of this project's design, development, and structure is to create an end-to-end Machine Learning Operations (MLOps) lifecycle to classify an individual's level of obesity based on their physical characteristics and eating habits.

Date Created 2024-08-13 (7 months ago)

Commits 57 (last one 4 months ago)

Stargazers 25 (0 this week)

Watchers 1 (0 this week)

Forks 3

License mit

Ranking

RepositoryStats indexes 634,548 repositories, of these rafaelgreca/e2e-mlops-project is ranked #626,239 (1st percentile) for total stargazers, and #558,875 for total watchers. Github reports the primary language for this repository as HTML, for repositories using this language it is ranked #16,219/16,566.

rafaelgreca/e2e-mlops-project is also tagged with popular topics, for these it's ranked: python (#23,300/23493), machine-learning (#8,365/8427), fastapi (#836/849), mlops (#437/442), continuous-integration (#334/335), continuous-delivery (#181/182)

Other Information

rafaelgreca/e2e-mlops-project has 1 open pull request on Github, 1 pull request has been merged over the lifetime of the repository.

All Topics

mlops loguru python fastapi pydantic end-to-end evidentlyai tabular-data machine-learning continuous-delivery lightgbm-classifier continuous-integration obesity-classification multiclass-classification

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Recent Commit History

57 commits on the default branch (master) since jan '22

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No issues have been posted

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The primary language is HTML but there's also others...

updated: 2025-03-24 @ 05:32am, id: 841989279 / R_kgDOMi-8nw