Data science concepts and techniques with applications / Usman Qamar, Muhammad Summair Raza.
2023
QA76.9.D343 Q36 2023
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Details
Title
Data science concepts and techniques with applications / Usman Qamar, Muhammad Summair Raza.
Author
Qamar, Usman, author.
Edition
Second edition.
ISBN
9783031174421 electronic book
3031174429 electronic book
9783031174414
3031174410
3031174429 electronic book
9783031174414
3031174410
Published
Cham : Springer, 2023.
Language
English
Description
1 online resource : illustrations (black and white).
Item Number
10.1007/978-3-031-17442-1 doi
Call Number
QA76.9.D343 Q36 2023
Dewey Decimal Classification
006.3/12
Summary
This textbook comprehensively covers both fundamental and advanced topics related to data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. The chapters of this book are organized into three parts: The first part (chapters 1 to 3) is a general 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 presentation of a wide range of applications and widely used techniques in data science. The second part, which has been updated and considerably extended compared to the first edition, is devoted to various techniques and tools applied in data science. Its chapters 4 to 10 detail data pre-processing, classification, clustering, text mining, deep learning, frequent pattern mining, and regression analysis. Eventually, the third part (chapters 11 and 12) present a brief introduction to Python and R, the two main data science programming languages, and shows in a completely new chapter practical data science in the WEKA (Waikato Environment for Knowledge Analysis), an open-source tool for performing different machine learning and data mining tasks. An appendix explaining the basic mathematical concepts of data science completes the book. This textbook is suitable for advanced undergraduate and graduate students as well as for industrial practitioners who carry out research in data science. They both will not only benefit from the comprehensive presentation of important topics, but also from the many application examples and the comprehensive list of further readings, which point to additional publications providing more in-depth research results or provide sources for a more detailed description of related topics. "This book delivers a systematic, carefully thoughtful material on Data Science." from the Foreword by Witold Pedrycz, U Alberta, Canada.
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Access limited to authorized users.
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Description based on print version record.
Added Author
Raza, Muhammad Summair, author.
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Data science concepts and techniques with applications.
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Table of Contents
1. Introduction
2. Applications of Data Science
3. Widely Used Techniques in Data Science Applications
4. Data Preprocessing
5. Classification
6. Clustering
7. Text Mining
8. Deep Learning
9. Frequent Pattern Mining
10. Regression Analysis
11. Data Science Programming Language
12. Practical Data Science with WEKA.
2. Applications of Data Science
3. Widely Used Techniques in Data Science Applications
4. Data Preprocessing
5. Classification
6. Clustering
7. Text Mining
8. Deep Learning
9. Frequent Pattern Mining
10. Regression Analysis
11. Data Science Programming Language
12. Practical Data Science with WEKA.