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Data Science Fundamentals and Practical Approaches

ebook

Learn how to process and analysis data using Python

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.


Expand title description text
Publisher: BPB Publications

OverDrive Read

  • ISBN: 9789389845662
  • Release date: June 2, 2020

EPUB ebook

  • ISBN: 9789389845662
  • File size: 11985 KB
  • Release date: June 2, 2020

Formats

OverDrive Read
EPUB ebook

Languages

English

Learn how to process and analysis data using Python

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.


Expand title description text