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.

heroku deployment html5

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54 Stars

8 Forks

54 Watchers

CSS Language

mit License

100 SrcLog Score

Cost to Build

$19.72M

Market Value

$27.88M

How is this calculated?

Growth over time

7 data points · 2022-09-01 → 2026-04-01

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What is the Nneji123/Serving-Machine-Learning-Models GitHub project? Description: "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.". Written in CSS. Explain what it does, its main use cases, key features, and who would benefit from using it.

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