Data Science Concepts and Techniques with Applications / by Usman Qamar, Muhammad Summair Raza.

Format:

Book

Author/Creator:

Qamar, Usman, author.

Raza, Muhammad Summair, author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Language:

English

Subjects (All):

Data mining.

Artificial intelligence.

Big data.

Data Mining and Knowledge Discovery.

Artificial Intelligence.

Big Data/Analytics.

Local Subjects:

Data Mining and Knowledge Discovery.

Artificial Intelligence.

Big Data/Analytics.

Physical Description:

1 online resource (XV, 196 pages) : 108 illustrations, 43 illustrations in color

Edition:

First edition 2020.

Contained In:

Springer Nature eBook

Place of Publication:

Singapore : Springer Singapore : Imprint: Springer, 2020.

System Details:

text file PDF

Summary:

This book comprehensively covers the topic of data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three sections: The first section is an introduction to data science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics. Followed by discussion on wide range of applications of data science and widely used techniques in data science. The second section is devoted to the tools and techniques of data science. It consists of data pre-processing, feature selection, classification and clustering concepts as well as an introduction to text mining and opining mining. And finally, the third section of the book focuses on two programming languages commonly used for data science projects id est Python and R programming language. Although this book primarily serves as a textbook, it will also appeal to industrial practitioners and researchers due to its focus on applications and references. The book is suitable for both undergraduate and postgraduate students as well as those carrying out research in data science. It can be used as a textbook for undergraduate students in computer science, engineering and mathematics. It can also be accessible to undergraduate students from other areas with the adequate background. The more advanced chapters can be used by postgraduate researchers intending to gather a deeper theoretical understanding.

Contents:

Introduction

Applications of Data Science

Widely used techniques in Data Science Applications

Data Pre-processing

Classification, Basic Concepts

Clustering

Text Mining

Data Science Programming Language.

Other Format:

Printed edition:

ISBN:

978-981-15-6133-7

9789811561337

Access Restriction:

Restricted for use by site license.