Data science is an interdisciplinary field encompassing scientific methods,
processes, and systems to extract knowledge or insights from data in
various forms, either structured or unstructured. It draws principles from
mathematics, statistics, information science, computer science, machine
learning, visualization, data mining, and predictive analytics. However, it is
fundamentally grounded in mathematics.
This book explains and applies the fundamentals of data science
crucial for technical professionals such as DBAs and d
evelopers who are
making career moves toward practicing data science. It is an example-
driven book providing complete Python coding examples to complement
and clarify data science concepts, and enrich the learning experience.
Coding examples include visualizations whenever appropriate. The book
is a necessary precursor to applying and implementing machine learning
algorithms, because it introduces the reader to foundational principles of
the science of data.