Docker and Python - Making Them Play Nicely and Securely for Data Science and ML

Explore best practices for integrating Docker with Python in data science and machine learning projects through this 40-minute PyCon US talk. Learn how to optimize Docker container builds for data-intensive applications, ensure security, and implement efficient deployment workflows. Gain confidence in adopting Docker for various data science, machine learning, and research projects. Discover key topics including the importance of Docker, Jupiter, security considerations, automation techniques, and valuable tips for seamless integration. Access accompanying slides for a comprehensive understanding of Docker and Python synergy in scientific computing environments.

Introduction
Why Docker
Jupiter
Best practices
Security
Automation
Top tips