Explore Docker integration with Jupyter Notebooks for enhanced reproducibility and remote execution of machine learning projects. Learn to create isolated, pre-defined environments using Docker, build custom images with essential Dockerfile commands, and deploy containers on remote machines. Gain insights into container registries, SSH access, and best practices for dockerizing Jupyter Notebooks, enabling seamless sharing and collaboration in data science workflows.
Overview
Syllabus
DagsHub
NIR BARAZIDA
Docker for Machine Learning
Docker Components
Container Registry
New Docker Project
Docker File
Useful Dockerfile Commands
Build Docker Image
Run Docker Container
SSH into a Container
Recap
Taught by
PyCon US
