What Is Docker In Data Science?
Docker boosts data science projects with reproducibility, portability, isolation & collaboration. Use Dockerfiles, build images & run containers with Docker Compose & Hub.
In the world of data science, reproducibility and consistency are key. Every data science project involves various dependencies: Python libraries, packages, datasets, and configurations. Docker helps to ensure that you can run your data science project seamlessly, whether you're working on your local machine, collaborating with a team, or deploying models in production. In this article, we’ll explore how Docker can enhance your data science workflows by creating a portable, reproducible, and consistent environment. 1. What Is Docker and Why Should You Use It in Data Science?...