From the course: Deploying Scalable Machine Learning for Data Science
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Example Docker build process
From the course: Deploying Scalable Machine Learning for Data Science
Example Docker build process
- [Narrator] We've gone through the process of analyzing and constructing a Dockerfile. Now I'd like to take a little bit of time just to show you how to build the Docker image and then run it interactively. So first I just want to show you my working environment. I have a directory here that I've called Docker_example and in it, I have two objects. I have a Dockerfile and then I have a directory called model where I would store my scripts for my machine learning model. What I'm most concerned about here is the Dockerfile so I'm going to cat that or list the Dockerfile. And what we'll notice here, I'll just scroll up a bit, is that our Dockerfiles starts with Ubuntu, creates a few labels that we'll use to keep track of our image, runs an apt-get to update the operating system and install some additional packages and then we'll run pip which is a Python installation program. We'll copy our code from our current directory into a model directory on the image. We'll expose a port for the…
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