Docker for Data Science

Building Scalable and Extensible Data Infrastructure Around the Jupyter Notebook Server

Häftad, Engelska, 2017

665 kr

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Beskrivning

Learn Docker "infrastructure as code" technology to define a system for performing standard but non-trivial data tasks on medium- to large-scale data sets, using Jupyter as the master controller. It is not uncommon for a real-world data set to fail to be easily managed.

Produktinformation

Utgivningsdatum:2017-08-25
Mått:155 x 235 x 20 mm
Vikt:462 g
Format:Häftad
Språk:Engelska
Antal sidor:257
Upplaga:17001
Förlag:APress
ISBN:9781484230114

Utforska kategorier

Databaser inom Data och IT
Artificiell intelligens inom Data och IT
Operativsystem inom Data och IT

Mer om författaren

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.

Innehållsförteckning

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.