Structuring Data Science Projects with Docker

Learn how to structure a data science project using Docker in this 13-minute video tutorial. Explore an advanced project structure designed to minimize friction when deploying models. Gain insights into the code overview, Docker image vulnerabilities, and the benefits of using Chainguard images. Discover the pros and cons of incorporating Docker into data science workflows, including the advantage of near-perfect environment replication and the learning curve associated with Docker. Access resources such as the recommended cookiecutter template and Pytorch Chainguard Image. Follow along with the step-by-step walkthrough to enhance your data science project organization and deployment strategies.

- Introduction:
- Overview:
- Code Overview:
- Docker Image Vulnerability:
- Chainguard Image:
- Pro and Con of Docker for Data Science: