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(as of Jun 22, 2025 21:22:07 UTC – Details)
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.
ASIN : B06X9JZNWG
Publisher : Springer
Accessibility : Learn more
Publication date : February 22, 2017
Edition : 1st ed. 2017
Language : English
File size : 15.4 MB
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 351 pages
ISBN-13 : 978-3319500171
Page Flip : Enabled
Part of series : Undergraduate Topics in Computer Science