Docker for Data Science

Teaches Docker principles with practical examples
Covers high-performance interactive computing with Jupyter
Presents a unique development method geared toward interactive computing

Teaches Docker principles with practical examples Covers high-performance interactive computing with Jupyter Presents a unique development method geared toward interactive computing

Autorentext
Joshua Cook is a mathematician. He writes code in Bash, C, and Python and has done pure and applied computational work in geo-spatial predictive modeling, quantum mechanics, semantic search, and artificial intelligence. He also has 10 years experience teaching mathematics at the secondary and post-secondary level. His research interests lie in high-performance computing, interactive computing, feature extraction, and reinforcement learning. He is always willing to discuss orthogonality or to explain why Fortran is the language of the future over a warm or cold beverage.

Zusammenfassung
Teaches Docker principles with practical examples
Covers high-performance interactive computing with Jupyter
Presents a unique development method geared toward interactive computing

Inhalt

Chapter 1: Introduction.- Chapter 2: Docker.- Chapter 3: Interactive Programming.- Chapter 4: Docker Engine.- Chapter 5: The Dockerfile.- Chapter 6: Docker Hub.- Chapter 7: The Opinionated Jupyter Stacks.- Chapter 8: The Data Stores.- Chapter 9: Docker Compose.- Chapter 10: Interactive Development.