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Books > Computing & IT > Applications of computing > Databases > Data mining
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Data Science in Theory and Practice - Techniques for Big Data Analytics and Complex Data Sets (Hardcover, 2nd Edition)
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Data Science in Theory and Practice - Techniques for Big Data Analytics and Complex Data Sets (Hardcover, 2nd Edition)
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DATA SCIENCE IN THEORY AND PRACTICE EXPLORE THE FOUNDATIONS OF DATA
SCIENCE WITH THIS INSIGHTFUL NEW RESOURCE Data Science in Theory
and Practice delivers a comprehensive treatment of the mathematical
and statistical models useful for analyzing data sets arising in
various disciplines, like banking, finance, health care,
bioinformatics, security, education, and social services. Written
in five parts, the book examines some of the most commonly used and
fundamental mathematical and statistical concepts that form the
basis of data science. The authors go on to analyze various data
transformation techniques useful for extracting information from
raw data, long memory behavior, and predictive modeling. The book
offers readers a multitude of topics all relevant to the analysis
of complex data sets. Along with a robust exploration of the theory
underpinning data science, it contains numerous applications to
specific and practical problems. The book also provides examples of
code algorithms in R and Python and provides pseudo-algorithms to
port the code to any other language. Ideal for students and
practitioners without a strong background in data science, readers
will also learn from topics like: Analyses of foundational
theoretical subjects, including the history of data science, matrix
algebra and random vectors, and multivariate analysis A
comprehensive examination of time series forecasting, including the
different components of time series and transformations to achieve
stationarity Introductions to both the R and Python programming
languages, including basic data types and sample manipulations for
both languages An exploration of algorithms, including how to write
one and how to perform an asymptotic analysis A comprehensive
discussion of several techniques for analyzing and predicting
complex data sets Perfect for advanced undergraduate and graduate
students in Data Science, Business Analytics, and Statistics
programs, Data Science in Theory and Practice will also earn a
place in the libraries of practicing data scientists, data and
business analysts, and statisticians in the private sector,
government, and academia.
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