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Essential Math for Data Science by Thomas Nield

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Summary

To succeed in data science you need some math proficiency. But not just any math. This common-sense guide provides a clear, plain English survey of the math you'll need in data science, including probability, statistics, hypothesis testing, linear algebra, machine learning, and calculus.

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Essential Math for Data Science by Thomas Nield

To succeed in data science you need some math proficiency. But not just any math. This common-sense guide provides a clear, plain English survey of the math you'll need in data science, including probability, statistics, hypothesis testing, linear algebra, machine learning, and calculus.

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Thomas Nield is the founder of Nield Consulting Group as well as an instructor at O'Reilly Media and University of Southern California. He enjoys making technical content relatable and relevant to those unfamiliar or intimidated by it. Thomas regularly teaches classes on data analysis, machine learning, mathematical optimization, and practical artificial intelligence. He's authored two books, including Getting Started with SQL (O'Reilly) and Learning RxJava (Packt).
SKU Unavailable
ISBN 13 9781098102937
ISBN 10 1098102932
Title Essential Math for Data Science
Author Thomas Nield
Condition Unavailable
Binding Type Paperback
Publisher O'Reilly Media
Year published 2022-06-10
Number of pages 350
Cover note Book picture is for illustrative purposes only, actual binding, cover or edition may vary.

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