Data scientists typically have their predictive models in a Python script file or notebook. In this video, learn how to create the machine learning model.
- [Instructor] Often, when working in a data science … or a machine learning team, you want … to standardize your environment. … Now it's common for data science teams … to use Anaconda, so let's start off with Miniconda … which is a slimmed down version of Conda … and let's say our dev environment requires … the following versions for pandas and Seaborn. … So I'm going to build my image, so docker build -t, … and I'm going to call this dev-env add dot. … And this'll take a couple of minutes … for it to download all for the different packages required. … So let me go ahead and clear my screen. … Now, it's common for teams to work from a shared drive … or a common network drive. … So for the sake of this example, … I'm going to say that my C drive is my shared drive. … Now, Windows has a hard time dealing with spaces in the path … so we need to enclose the path with a double quote. … So in this example you're going … to be using Docker's Volumes, … so docker container run … - it -v for volumes. …
- Why Docker is gaining prominence
- Running a container
- Docker under the hood
- Working with Dockerfiles
- Uploading images to Docker Hub
- Common use cases for Docker