How can you deploy a machine learning model into production? That's where we use Flask, an awesome tool for model deployment in machine learning.
Steps to deploy a machine learning model with Flask and Docker We will use Docker as a container to deploy the Flask app. A container is similar to a virtual machine except that it does not have its own resources. Rather, it shares them with the host machine. This helps to deploy the ...
Flask is a micro web framework written in Python. It can create a REST API that allows you to send data, and receive a prediction as a response.
FlaskandFastAPIare generic Python web frameworks used to deploy a wide variety of Python applications. Because of their simplicity and widespread adoption, many developers use them to deploy and run AI models in production. However, significant drawbacks to this approach include the following: General...
In this hands-on tutorial, I will show you how to deploy a simple Flask application in a Docker container on AWS Elastic Beanstalk and how to add a logging functionality, so your users will be able to see what’s happening behind the scenes. The application wil...
In this tutorial, I’m going to show you, step by step, how to create and deploy your machine learning model and UI on Heroku. I’ll use this drag-and-drop image interface that I created for the…
Make sure you set the environment variable FLASK_ENV to production if you are going to deploy the app publicly. Contributing We welcome all forms of contributions. We are especially interested in the following: Bug fixes Enhancements or additional features Improvements to the model, or expansion ...
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....
A tensor, in a machine learning context, refers to an n-dimensional array. A tape-based autograd means that Pytorch uses reverse-mode automatic differentiation, which is a mathematical technique to compute derivatives (or gradients) effectively using a computer. Since diving into these mathematics ...
In this tutorial, you created a deep learning model to be served as a REST API using Flask. It put the application inside a Docker container, uploaded the container to Docker Hub, and deployed it with Kubernetes. Then, with just a few commands, Kubermatic Kubernetes Platform deployed the app...