Serving Machine Learning Models

screenshot of Serving Machine Learning Models
flask
html

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.

Overview

This repository provides instructions, template source code, and examples for serving and deploying machine learning models using various frameworks and applications such as Docker, Flask, FastAPI, BentoML, Streamlit, and MLflow. It also includes code on how to deploy machine learning models as an Android app and how to deploy applications to various cloud platforms (AWS, Heroku, Vercel). The repository covers topics like version control, testing, and working with Docker.

Features

  • Serving Models with FastAPI: Learn how to serve machine learning models using FastAPI.
  • Serving Models with Flask: Understand how to deploy machine learning models using Flask.
  • Serving Models with BentoML: Discover the process of serving models using BentoML.
  • Serving Models with Mlflow: Learn how to serve models using MLflow.
  • Serving Models with Streamlit: Understand how to deploy models using Streamlit.
  • Serving Models as Desktop/Mobile Applications: Learn how to deploy machine learning models as desktop or mobile applications.
  • How to Test your models and applications with Pytest: Explore how to perform testing on machine learning models and applications using Pytest.
  • Working with Docker: Understand the process of working with Docker for serving machine learning models.
  • Deploying your applications to AWS and Heroku: Learn how to deploy your applications to AWS and Heroku.
  • Using Github Actions and Heroku for CI/CD: Discover how to use Github Actions and Heroku for Continuous Integration and Continuous Deployment.
flask
Flask

Flask is a lightweight and popular web framework for Python, known for its simplicity and flexibility. It is widely used to build web applications, providing a minimalistic approach to web development with features like routing, templates, and support for extensions.

html
HTML

HTML templates are pre-designed and pre-built web pages that can be customized and used as a basis for building websites. They often include common elements such as headers, footers, menus, and content sections, and can be easily edited using HTML and CSS to fit specific branding and content needs.

docker
Docker

A website that uses Docker for containerization to streamline development, testing, and deployment workflows. This includes features such as containerization of dependencies, automated builds and deployments, and container orchestration to ensure scalability and availability.