Data Science Fundamentals & Practical Approaches

By:

Nandi Gypsy

Publication details: BPB Publications 2020 New DelhiDescription: 634ISBN:

9789389845662

Subject(s):

Data Science

DDC classification:

005.74015 NAN

Summary: This book introduces the fundamental concepts of Data Science, which has proved to be a major game-changer in business solving problems. Topics covered in the book include fundamentals of Data Science, data preprocessing, data plotting and visualization, statistical data analysis, machine learning for data analysis, time-series analysis, deep learning for Data Science, social media analytics, business analytics, and Big Data analytics. The content of the book describes the fundamentals of each of the Data Science related topics together with illustrative examples as to how various data analysis techniques can be implemented using different tools and libraries of Python programming language. Each chapter contains numerous examples and illustrative output to explain the important basic concepts. An appropriate number of questions is presented at the end of each chapter for self-assessing the conceptual understanding. The references presented at the end of every chapter will help the readers to explore more on a given topic. Source: https://in.bpbonline.com/products/data-science-python-programming-book-ebook?_pos=1&_sid=ecff3c0d3&_ss=r

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Item type	Current library	Collection	Call number	Status	Date due	Barcode
Book	Main Library Analytics	Reference book	005.74015 NAN (Browse shelf(Opens below))	Available		119447

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This book introduces the fundamental concepts of Data Science, which has proved to be a major game-changer in business solving problems.
Topics covered in the book include fundamentals of Data Science, data preprocessing, data plotting and visualization, statistical data analysis, machine learning for data analysis, time-series analysis, deep learning for Data Science, social media analytics, business analytics, and Big Data analytics. The content of the book describes the fundamentals of each of the Data Science related topics together with illustrative examples as to how various data analysis techniques can be implemented using different tools and libraries of Python programming language.
Each chapter contains numerous examples and illustrative output to explain the important basic concepts. An appropriate number of questions is presented at the end of each chapter for self-assessing the conceptual understanding. The references presented at the end of every chapter will help the readers to explore more on a given topic.

Source: https://in.bpbonline.com/products/data-science-python-programming-book-ebook?_pos=1&_sid=ecff3c0d3&_ss=r

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