Nneji123 / Serving-Machine-Learning-Models

This repository contains instructions, template source code and examples on how to serve/deploy machine learning models using various frameworks and applications such as Docker, Flask, FastAPI, BentoML, Streamlit, MLflow and even code on how to deploy your machine learning model as an android app.

Nneji123
Nneji123
Date Created 2022-07-11 (about a year ago)
Commits 81 (last one about a year ago)
Stargazers 52 (0 this week)
Watchers 0 (0 this week)
Forks 10
License mit
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RepositoryStats indexes 535,551 repositories, of these Nneji123/Serving-Machine-Learning-Models is ranked #421,227 (21st percentile) for total stargazers, and #532,808 for total watchers. Github reports the primary language for this repository as CSS, for repositories using this language it is ranked #4,144/5,352.

Nneji123/Serving-Machine-Learning-Models is also tagged with popular topics, for these it's ranked: machine-learning (#6,165/7379),  docker (#4,820/5789),  css (#2,513/3084),  flask (#791/957),  html5 (#660/825),  fastapi (#472/653),  webapp (#487/610),  actions (#383/468),  deployment (#355/415),  heroku (#331/401),  mlops (#306/388),  streamlit (#219/333)

Other Information

Nneji123/Serving-Machine-Learning-Models has 5 open pull requests on Github, 0 pull requests have been merged over the lifetime of the repository.

Homepage URL: https://nneji123.github.io/Serving-Machine-Learning-Models/

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

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Nneji123/Serving-Machine-Learning-Models

updated: 2024-04-16 @ 02:23am, id: 512852641 / R_kgDOHpGCoQ