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Practical Data Analysis

You're reading from   Practical Data Analysis Pandas, MongoDB, Apache Spark, and more

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Product type Paperback
Published in Sep 2016
Publisher
ISBN-13 9781785289712
Length 338 pages
Edition 2nd Edition
Languages
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Authors (2):
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Hector Cuesta Hector Cuesta
Author Profile Icon Hector Cuesta
Hector Cuesta
Dr. Sampath Kumar Dr. Sampath Kumar
Author Profile Icon Dr. Sampath Kumar
Dr. Sampath Kumar
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Toc

Table of Contents (16) Chapters Close

Preface 1. Getting Started 2. Preprocessing Data FREE CHAPTER 3. Getting to Grips with Visualization 4. Text Classification 5. Similarity-Based Image Retrieval 6. Simulation of Stock Prices 7. Predicting Gold Prices 8. Working with Support Vector Machines 9. Modeling Infectious Diseases with Cellular Automata 10. Working with Social Graphs 11. Working with Twitter Data 12. Data Processing and Aggregation with MongoDB 13. Working with MapReduce 14. Online Data Analysis with Jupyter and Wakari 15. Understanding Data Processing using Apache Spark

Visualization in art


Visual artists have been using computer-based tools in visual arts rather than traditional art media more often. Artists often use computers for capturing or creating images and forms, editing those images and forms, and printing the images. In turn, they integrate digital technologies and algorithmic art with many traditional arts, and as a result, new media visuals are created, but they are a common theme between the one who prepares the scientific visualization and the artist.

On the other hand, computer usage has blurred the differences between photographers, illustrators, photo editors, handicraft artists, and 3-D modelers. Sophisticated visualization tools are required to reduce the differences between them. This leads handicrafts to become computer-aided imagery, photographers to become digital artists, and illustrators to become animators. While solving visual artists' professional tasks, the visualization processes and experiences of visual artists are unique...

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