Docker for Data Science Building Scalable and Extensible Data Infrastructure Around the Jupyter Notebook Server

Docker for Data Science Building Scalable and Extensible Data Infrastructure Around the Jupyter Notebook Server / by Joshua Cook.

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. The set may not fit...

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Bibliographic Details
Main Author: Cook, Joshua (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Berkeley, CA : Apress : Imprint: Apress, 2017.
Edition:1st ed. 2017.
Series:Springer eBook Collection.
Subjects:
Big data.
Artificial intelligence.
Open source software.
Computer programming.
Python (Computer program language).
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • 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.

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