Algorithms for Data Science

Algorithms for Data Science

Sale price  $89.99 Regular price $99.99
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Algorithms for Data Science

Algorithms for Data Science

Sale price  $89.99 Regular price $99.99

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Algorithms for Data Science

Brian Steele | John Chandler | Swarna Reddy

Computers / Data Science / Data Analytics

Unites theory, algorithm design, and practical data analysis for simplicity and clarity of content

Contains more than twenty detailed and carefully crafted Python tutorials

Each chapter includes exercises of varying levels of difficulty

Uses publicly available data sets throughout the book


Brian Steele is a full professor of Mathematics at the University of Montana and a Senior Data Scientist for SoftMath Consultants, LLC. Dr. Steele has published on the EM algorithm, exact bagging, the bootstrap, and numerous statistical applications. He teaches data analytics and statistics and consults on a wide variety of subjects related to data science and statistics.

John Chandler has worked at the forefront of marketing and data analysis since 1999. He has worked with Fortune 100 advertisers and scores of agencies, measuring the effectiveness of advertising and improving performance. Dr. Chandler joined the faculty at the University of Montana School of Business Administration as a Clinical Professor of Marketing in 2015 and teaches classes in advanced marketing analytics and data science. He is one of the founders and Chief Data Scientist for Ars Quanta, a Seattle-based data science consultancy.

Dr. Swarna Reddy is the founder, CEO, and a Senior Data Scientist for SoftMath Consultants, LLC and serves as a faculty affiliate with the Department of Mathematical Sciences at the University of Montana. Her area of expertise is computational mathematics and operations research. She is a published researcher and has developed computational solutions across a wide variety of areas spanning bioinformatics, cybersecurity, and business analytics.



Publication Date: 27 December 2016
Publisher: Springer International Publishing
Imprint: Springer
ISBN-13: 9783319457956
Format: Hardback
Page Count: 430

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