In this tutorial, we will learn Machine Learning Prediction in Real Time Using Docker and Python REST APIs with Flask. Here is a quick example of a Docker container and REST APIs to perform online inference
The idea of this article is to do a quick and easy build of a Docker container to perform online inference with trained machine learning models using Python APIs with Flask. Before reading this article, do not hesitate to read Why use Docker for Machine Learning, Quick Install and First Use of Docker, and Build and Run a Docker Container for your Machine Learning Model in which we learn how to use Docker to perform model training and batch inference.
Batch inference is great when you have time to compute your predictions. Let’s imagine you need real time predictions. In this case, batch inference is not more suitable and we need online inference. Many applications would not work or would not be very useful without online predictions such as autonomous vehicles, fraud detection, high-frequency trading, applications based on localization data, object recognition and tracking or brain computer interfaces. Sometimes, the prediction needs to be provided in milliseconds.
Following the second video about Docker basics, in this video, I explain Docker architecture and explain the different building blocks of the docker engine; docker client, API, Docker Daemon. I also explain what a docker registry is and I finish the video with a demo explaining and illustrating how to use Docker hub.
Docker Architecture Overview & Docker Components. This ultimate guide revolves around the underlying technologies used by Docker Containers to provide effective containerisation services to its users. It explains the entire Docker architecture and its components using intuitive diagrams.
Welcome to this on Docker Tutorial for Beginners. In this video provides an Introduction on C++ development with Docker containers. So we will see How to ship C++ Programs in Docker.
“Docker: Understanding Docker Architecture and Components”, The First thing we are going to do is to run the “docker run hello-world” command. This command tries to find the “hello-world” image locally and if not found, it then downloads an image from the docker hub and runs the container out of this image.
This entry-level guide will tell you why and how to Dockerize your WordPress projects.