karan842 / mlops-best-practices

Practical guide to build end-to-end machine learning pipeline and deploy your model in production,

Date Created 2023-04-20 (about a year ago)

Commits 61 (last one about a year ago)

Stargazers 60 (1 this week)

Watchers 2 (0 this week)

Forks 13

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Ranking

RepositoryStats indexes 584,353 repositories, of these karan842/mlops-best-practices is ranked #409,904 (30th percentile) for total stargazers, and #478,709 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #10,492/17,098.

karan842/mlops-best-practices is also tagged with popular topics, for these it's ranked: python (#16,837/22011), machine-learning (#6,101/7926), devops (#1,069/1323), azure (#834/1072), data (#724/975), numpy (#417/537), mlops (#315/413), sklearn (#102/123)

Other Information

Homepage URL: https://medium.com/@karanshingde/machine-learning-in-production-your-comprehensive-101-practical-guide-c7de0b5ad011

All Topics

data azure mlops numpy devops mlflow python sklearn xgboost lightgbm machine-learning

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

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updated: 2024-11-20 @ 01:50pm, id: 630403288 / R_kgDOJZMw2A