Visualizing Streaming Data (O'Reilly)
Monday, 20 August 2018

This practical guide shows different ways to create visualizations that bring context and a sense of time to streaming text data. Author Anthony Aragues introduces the concepts and tools needed to build visualizations for analyzing data as it arrives.The topics ride the line between design and development because they are both integral in presenting comprehensible data.

<ASIN:1492031852>

 

Author: Anthony Aragues
Publisher: O'Reilly
Date: July 2018
Pages: 200
ISBN: 978-1492031857
Print: 1492031852
Kindle: B07DGKKG52
Audience: Data scientists and developers
Level: Intermediate
Category: Data Science

 

 

  • Determine your company’s goals for visualizing streaming data
  • Identify key data sources and learn how to stream them
  • Learn practical methods for processing streaming data
  • Build a client application for interacting with events, logs, and records
  • Explore common components for visualizing streaming data
  • Consider analysis concepts for developing your visualization
  • Define the dashboard’s layout, flow direction, and component movement
  • Improve visualization quality and productivity through collaboration
  • Explore use cases including security, IoT devices, and application data

For recommendations of Data Science books see Reading Your Way Into Big Data in our Programmer's Bookshelf section.

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Artificial Intelligence, Machine Learning, and Deep Learning (Mercury Learning)

Author: Oswald Campesato
Publisher: Mercury Learning
Date: February 2020
Pages: 300
ISBN: 978-1683924678
Print: 1683924673
Kindle: B084P1K9YP
Audience: Developers interested in machine learning
Rating: 4
Reviewer: Mike James

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Author: Al Sweigart
Publisher: No Starch Press
Date: June 2021
Pages: 432
ISBN: 978-1718501249
Print: 1718501242
Kindle: B08FH9FV7M
Audience: Novice Python developers
Rating: 4
Reviewer: Lucy Black
A project book? A good way to learn Python?


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