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1 - Introduction to Information Theory and Data Science.

Published online by Cambridge University Press:  22 March 2021

By
Miguel R. D. Rodrigues ,
Stark C. Draper ,
Waheed U. Bajwa  and
Yonina C. Eldar
Edited by
Miguel R. D. Rodrigues  and
Yonina C. Eldar
Miguel R. D. Rodrigues
Affiliation:
University College London
Yonina C. Eldar
Affiliation:
Weizmann Institute of Science, Israel
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Summary

The purpose of this chapter is to set the stage for the book and for the upcoming chapters. We first overview classical information-theoretic problems and solutions. We then discuss emerging applications of information-theoretic methods in various data-science problems and, where applicable, refer the reader to related chapters in the book. Throughout this chapter, we highlight the perspectives, tools, and methods that play important roles in classic information-theoretic paradigms and in emerging areas of data science. Table 1.1 provides a summary of the different topics covered in this chapter and highlights the different chapters that can be read as a follow-up to these topics.

Keywords

information theorysource codingchannel codingcommunicationcompressiondata representationdata acquisitiondata analysisdata processingstatisticsmachine learning
Type
Chapter
Information
Information-Theoretic Methods in Data Science , pp. 1 - 43
Publisher: Cambridge University Press
Print publication year: 2021

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To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

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