Data Science Concepts And Techniques With Applications

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Data Science Concepts And Techniques With Applications

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Author : Usman Qamar
language : en
Publisher: Springer Nature
Release Date : 2020-06-08

Data Science Concepts And Techniques With Applications written by Usman Qamar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-08 with Computers categories.

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 i.e. 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.

Introduction To Data Science

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Author : Laura Igual
language : en
Publisher: Springer Nature
Release Date : 2024-04-12

Introduction To Data Science written by Laura Igual and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-12 with Computers categories.

This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the interdisciplinary field of data science. The coverage spans key concepts from statistics, machine/deep learning and responsible data science, useful techniques for network analysis and natural language processing, and practical applications of data science such as recommender systems or sentiment analysis. Topics and features: Provides numerous practical case studies using real-world data throughout the book Supports understanding through hands-on experience of solving data science problems using Python Describes concepts, techniques and tools for statistical analysis, machine learning, graph analysis, natural language processing, deep learning and responsible data science Reviews a range of applications of data science, including recommender systems and sentiment analysis of text data Provides supplementary code resources and data at an associated website This practically-focused textbook provides an ideal introduction to the field for upper-tier undergraduate and beginning graduate students from computer science, mathematics, statistics, and other technical disciplines. The work is also eminently suitable for professionals on continuous education short courses, and to researchers following self-study courses.

Data Analytics

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Author : Mohiuddin Ahmed
language : en
Publisher: CRC Press
Release Date : 2018-09-28

Data Analytics written by Mohiuddin Ahmed and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-28 with Big data categories.

Large data sets arriving at every increasing speeds require a new set of efficient data analysis techniques. This book provides a broad picture on the concepts, techniques, applications, and open research directions in this area. --

Data Science

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Author : Qurban A Memon
language : en
Publisher: CRC Press
Release Date : 2019-09-26

Data Science written by Qurban A Memon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-26 with Computers categories.

The aim of this book is to provide an internationally respected collection of scientific research methods, technologies and applications in the area of data science. This book can prove useful to the researchers, professors, research students and practitioners as it reports novel research work on challenging topics in the area surrounding data science. In this book, some of the chapters are written in tutorial style concerning machine learning algorithms, data analysis, information design, infographics, relevant applications, etc. The book is structured as follows: • Part I: Data Science: Theory, Concepts, and Algorithms This part comprises five chapters on data Science theory, concepts, techniques and algorithms. • Part II: Data Design and Analysis This part comprises five chapters on data design and analysis. • Part III: Applications and New Trends in Data Science This part comprises four chapters on applications and new trends in data science.

Introduction To Data Science

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Author : Laura Igual
language : en
Publisher: Springer
Release Date : 2017-02-22

Introduction To Data Science written by Laura Igual and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-22 with Computers categories.

This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.

Data Mining For Business Analytics

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Author : Galit Shmueli
language : en
Publisher: John Wiley & Sons
Release Date : 2016-05-09

Data Mining For Business Analytics written by Galit Shmueli and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-09 with Mathematics categories.

Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® presents an applied and interactive approach to data mining. Featuring hands-on applications with JMP Pro®, a statistical package from the SAS Institute, the book uses engaging, real-world examples to build a theoretical and practical understanding of key data mining methods, especially predictive models for classification and prediction. Topics include data visualization, dimension reduction techniques, clustering, linear and logistic regression, classification and regression trees, discriminant analysis, naive Bayes, neural networks, uplift modeling, ensemble models, and time series forecasting. Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® also includes: Detailed summaries that supply an outline of key topics at the beginning of each chapter End-of-chapter examples and exercises that allow readers to expand their comprehension of the presented material Data-rich case studies to illustrate various applications of data mining techniques A companion website with over two dozen data sets, exercises and case study solutions, and slides for instructors www.dataminingbook.com Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® is an excellent textbook for advanced undergraduate and graduate-level courses on data mining, predictive analytics, and business analytics. The book is also a one-of-a-kind resource for data scientists, analysts, researchers, and practitioners working with analytics in the fields of management, finance, marketing, information technology, healthcare, education, and any other data-rich field.

Introduction To Data Science

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Author : Laura Igual
language : en
Publisher: Springer
Release Date : 2024-04-25

Introduction To Data Science written by Laura Igual and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-25 with Computers categories.

This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the interdisciplinary field of data science. The coverage spans key concepts from statistics, machine/deep learning and responsible data science, useful techniques for network analysis and natural language processing, and practical applications of data science such as recommender systems or sentiment analysis. Topics and features: Provides numerous practical case studies using real-world data throughout the book Supports understanding through hands-on experience of solving data science problems using Python Describes concepts, techniques and tools for statistical analysis, machine learning, graph analysis, natural language processing, deep learning and responsible data science Reviews a range of applications of data science, including recommender systems and sentiment analysis of text data Provides supplementary code resources and data at an associated website This practically-focused textbook provides an ideal introduction to the field for upper-tier undergraduate and beginning graduate students from computer science, mathematics, statistics, and other technical disciplines. The work is also eminently suitable for professionals on continuous education short courses, and to researchers following self-study courses.

Data Science

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Author : Pallavi Chavan
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2022-07

Data Science written by Pallavi Chavan and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07 with Big data categories.

"The proposed book covers the topic of data science in a very comprehensive manner and synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The book starts from the basic concepts of data science; it highlights the types of data, its use and its importance, followed by discussion on a wide range of applications of data science and widely used techniques in data science. Key features: provides an internationally respected collection of scientific research methods, technologies and applications in the area of data science, presents predictive outcomes by applying data science techniques on real life applications, provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods, and gives the reader variety of intelligent applications that can be designed using data science and its allied fields. The book is aimed primarily at advanced undergraduates and graduates studying machine learning and data science. Researchers and professionals will also find this book useful"--

Introduction To Data Science Concepts And Applications

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Author : RENATA. SLOANE
language : en
Publisher: Independently Published
Release Date : 2025-05-20

Introduction To Data Science Concepts And Applications written by RENATA. SLOANE and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-20 with Computers categories.

Introduction to Data Science Concepts and Applications is the perfect starting point for anyone looking to understand the fundamentals of data science and its real-world applications. This book provides a comprehensive overview of the key concepts, tools, and methodologies used in data science, helping you build a solid foundation in the field. Whether you're new to data science or looking to expand your knowledge, this guide will walk you through the essential principles and demonstrate how data science can drive decision-making and innovation across various industries. Inside, you will discover: What is Data Science?: Get an introduction to the field of data science, including its history, evolution, and its role in today's data-driven world. Understand how data science combines statistics, programming, and domain expertise to extract actionable insights from data. Key Concepts in Data Science: Learn about core concepts such as data exploration, data cleaning, data visualization, statistical analysis, and machine learning. Understand how these concepts come together to form a comprehensive data science workflow. Tools and Technologies: Explore the most popular tools and technologies used in data science, including programming languages like Python and R, libraries like pandas, NumPy, and scikit-learn, and platforms for visualization like Matplotlib and Tableau. Data Collection and Preprocessing: Dive into how data is collected, cleaned, and prepared for analysis. Learn the importance of handling missing data, outliers, and data normalization, and discover best practices for building clean datasets. Exploratory Data Analysis (EDA): Understand how to conduct exploratory data analysis to identify patterns, relationships, and trends in data using visualizations, descriptive statistics, and basic modeling techniques. Introduction to Machine Learning: Get an overview of machine learning algorithms, including supervised and unsupervised learning, classification, regression, clustering, and more. Learn how data scientists use these techniques to build predictive models. Data Science in Real-World Applications: Learn how data science is applied across various industries, including healthcare (predicting disease outcomes), finance (fraud detection), marketing (customer segmentation), and e-commerce (recommendation systems). Ethics and Challenges in Data Science: Understand the ethical considerations in data science, such as data privacy, bias, and transparency, and learn about the challenges data scientists face in dealing with incomplete data, high dimensionality, and computational limits. Why This Book Is Essential: Clear and Structured Introduction: Provides a well-organized guide to the concepts, tools, and applications that form the foundation of data science. Practical Insights: Focuses on how data science techniques are applied in real-world scenarios to solve business and societal problems. Tools and Frameworks Overview: Introduces the most widely-used tools and frameworks in the industry, preparing you for hands-on learning. Real-World Case Studies: Includes industry-specific case studies that show how data science has transformed sectors such as healthcare, finance, marketing, and technology. Whether you're a student, professional, or someone looking to transition into the field of data science, Introduction to Data Science Concepts and Applications will equip you with the foundational knowledge you need to begin your journey in this exciting and rapidly growing field.

Mastering Data Science And Big Data Analytics

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Author : Nikhilesh Mishra
language : en
Publisher: Independently Published
Release Date : 2023-08-25

Mastering Data Science And Big Data Analytics written by Nikhilesh Mishra and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-25 with categories.

Embark on an illuminating voyage through the captivating landscape of "Mastering Data Science and Big Data Analytics: Concepts, Techniques, and Application" From foundational principles to advanced methodologies, this comprehensive guide empowers you with the wisdom and expertise to navigate the intricate world of data science and big data analytics. Explore the fundamental concepts of data science, from data acquisition to predictive modeling. Dive deep into cutting-edge techniques, including exploratory data analysis and machine learning. Gain practical insights from real-world data analysis projects spanning diverse industries. Uncover the ethical considerations and societal implications of data-driven decision-making. Enhance your growth potential with an exclusive section dedicated to interviews and interviewers, providing valuable insights and skills that amplify your journey towards success. Whether you're a budding enthusiast or a seasoned practitioner, "Mastering Data Science and Big Data Analytics: Concepts, Techniques, and Applications" empowers you to elevate your expertise and become a visionary in the realm of data-driven innovation. Seize the opportunity-secure your copy today and embark on a transformative journey of knowledge and exploration!