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Creating Augmented and Virtual Realities
book

Creating Augmented and Virtual Realities

by Erin Pangilinan, Steve Lukas, Vasanth Mohan
April 2019
Intermediate to advanced content levelIntermediate to advanced
370 pages
10h 23m
English
O'Reilly Media, Inc.
Content preview from Creating Augmented and Virtual Realities

Chapter 9. Data and Machine Learning Visualization Design and Development in Spatial Computing

Introduction

Data and machine learning visualization are transforming the future of the workplace. Framing design principles is valuable. Companies such as VR Fund–backed company, Virtualitics, which was founded by Caltech PhDs, raise large rounds of funding based on good design principles. There are also many other data visualization independent consultancies popping up across all spatial computing platforms. Many of these are within the businesses service sphere with significantly large datasets, in the B2B verticals of fintech (finance tech), health technology, and biotech.

We begin this chapter by discussing the relevance of the topic to the users experiencing data and machine learning visualization applications. We then offer a framework to consider for identifying useful purposes that make the topic unique to spatial computing versus any other platform. We outline our goals to understand, define, and set data and machine visualization design and development principles in embodied reality. Then, we discuss various challenges with data and machine learning visualization in XR, describing various examples of industry use cases for data and machine learning visualization built on top of open source data and frameworks (though some interesting work has also been done with open source frameworks and proprietary data). Toward the end of this chapter, we ...

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Publisher Resources

ISBN: 9781492044185Errata PageSupplemental Content