Communication Principles For Data Science

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Communication Principles For Data Science
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Author : Changho Suh
language : en
Publisher:
Release Date : 2023
Communication Principles For Data Science written by Changho Suh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
This book introduces the basic principles underlying the design and analysis of the digital communication systems that have heralded the information revolution. One major goal of the book is to demonstrate the role of the digital communication principles in a wide variety of data science applications, including community detection, computational biology, speech recognition and machine learning. One defining feature of this book is to make an explicit connection between the communication principles and data science problems, as well as to succinctly deliver the "story" of how the communication principles play a role for trending data science applications. All the key "plots" involved in the story are coherently developed with the help of tightly coupled exercise problem sets, and the associated fundamentals are explored mostly from first principles. Another key feature is that it includes programming implementation of a variety of algorithms inspired by fundamentals, together with a brief tutorial of the used programming tools. The implementation is based on Python and TensorFlow. This book does not follow a traditional book-style organization, but is streamlined via a series of lecture notes that are intimately related, centered around coherent storylines and themes. It serves as a textbook mainly for a junior- or senior-level undergraduate course, yet is also suitable for a first-year graduate course. Readers benefit from having a good background in probability and random processes, and basic familiarity with Python. But the background can be supplemented by almost self-contained materials, as well as by numerous exercise problems intended for elaborating on non-trivial concepts. In addition, Part III for data science applications should provide motivation and insights to students and even professional scientists who are interested in the field.
Communication Principles For Data Science
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Author : Changho Suh
language : en
Publisher: Springer Nature
Release Date : 2023-06-12
Communication Principles For Data Science written by Changho Suh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-12 with Computers categories.
This book introduces the basic principles underlying the design and analysis of the digital communication systems that have heralded the information revolution. One major goal of the book is to demonstrate the role of the digital communication principles in a wide variety of data science applications, including community detection, computational biology, speech recognition and machine learning. One defining feature of this book is to make an explicit connection between the communication principles and data science problems, as well as to succinctly deliver the “story” of how the communication principles play a role for trending data science applications. All the key “plots” involved in the story are coherently developed with the help of tightly coupled exercise problem sets, and the associated fundamentals are explored mostly from first principles. Another key feature is that it includes programming implementation of a variety of algorithms inspired by fundamentals, together with a brief tutorial of the used programming tools. The implementation is based on Python and TensorFlow. This book does not follow a traditional book-style organization, but is streamlined via a series of lecture notes that are intimately related, centered around coherent storylines and themes. It serves as a textbook mainly for a junior- or senior-level undergraduate course, yet is also suitable for a first-year graduate course. Readers benefit from having a good background in probability and random processes, and basic familiarity with Python. But the background can be supplemented by almost self-contained materials, as well as by numerous exercise problems intended for elaborating on non-trivial concepts. In addition, Part III for data science applications should provide motivation and insights to students and even professional scientists who are interested in the field.
The Data Science Handbook
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Author : Field Cady
language : en
Publisher: John Wiley & Sons
Release Date : 2024-10-31
The Data Science Handbook written by Field Cady 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 2024-10-31 with Computers categories.
Practical, accessible guide to becoming a data scientist, updated to include the latest advances in data science and related fields. Becoming a data scientist is hard. The job focuses on mathematical tools, but also demands fluency with software engineering, understanding of a business situation, and deep understanding of the data itself. This book provides a crash course in data science, combining all the necessary skills into a unified discipline. The focus of The Data Science Handbook is on practical applications and the ability to solve real problems, rather than theoretical formalisms that are rarely needed in practice. Among its key points are: An emphasis on software engineering and coding skills, which play a significant role in most real data science problems. Extensive sample code, detailed discussions of important libraries, and a solid grounding in core concepts from computer science (computer architecture, runtime complexity, and programming paradigms). A broad overview of important mathematical tools, including classical techniques in statistics, stochastic modeling, regression, numerical optimization, and more. Extensive tips about the practical realities of working as a data scientist, including understanding related jobs functions, project life cycles, and the varying roles of data science in an organization. Exactly the right amount of theory. A solid conceptual foundation is required for fitting the right model to a business problem, understanding a tool’s limitations, and reasoning about discoveries. Data science is a quickly evolving field, and this 2nd edition has been updated to reflect the latest developments, including the revolution in AI that has come from Large Language Models and the growth of ML Engineering as its own discipline. Much of data science has become a skillset that anybody can have, making this book not only for aspiring data scientists, but also for professionals in other fields who want to use analytics as a force multiplier in their organization.
Data Science For Decision Makers
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Author : Erik Herman
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-12-31
Data Science For Decision Makers written by Erik Herman and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-31 with Computers categories.
Data Science for Decision Makers is an essential guide for executives, managers, entrepreneurs, and anyone seeking to harness the power of data to drive business success. In today's fast-paced and increasingly digital world, the ability to make informed decisions based on data-driven insights is vital. This book serves as a bridge between the complex world of data science and the strategic decision-making process, providing readers with the knowledge and tools they need to leverage data effectively. With a clear focus on practical application, this book demystifies key concepts in data science, from data collection and analysis to predictive modeling and visualization. Via real-world examples, case studies, and actionable insights, readers will learn how to extract insights from data and translate them into actionable strategies that drive organizational growth. Written in a reader-friendly manner, this book caters to both novice and experienced professionals alike. Whether you're a seasoned executive looking to sharpen your strategic acumen or a manager seeking to enhance your team's data literacy, this essential reference provides the necessary foundation to navigate the complex landscape of data science with confidence.
Data Science For Undergraduates
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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2018-10-11
Data Science For Undergraduates written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-11 with Education categories.
Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.
Enhancing Business Communications And Collaboration Through Data Science Applications
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Author : Geada, Nuno
language : en
Publisher: IGI Global
Release Date : 2023-03-21
Enhancing Business Communications And Collaboration Through Data Science Applications written by Geada, Nuno and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-21 with Business & Economics categories.
Digital evolution has become increasingly present in our lives, whether on cellphones, computers, watches, or other appliances. As a result of the wide access we have to the digital world, the amount of data generated daily is vast. This density of information generated at every moment can be the insight needed for the success of an organization. Much is said about data-based decision-making to generate the best results. The new capabilities of data intelligence unleashed by the emergence of cloud computing and artificial intelligence make it one of the most promising areas of digital transformation change management. Enhancing Business Communications and Collaboration Through Data Science Applications provides relevant theoretical frameworks and the latest empirical research findings in the area. It is written for professionals who wish to improve their understanding of the strategic role of trust at different levels of the information and knowledge society. Covering topics such as data science, online business communication, and user-centered design, this premier reference source is an ideal resource for business managers and leaders, entrepreneurs, data scientists, data analysts, sociologists, students and educators of higher education, librarians, researchers, and academicians.
Exploring Data Science Concepts Techniques And Tools
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Author : Dr. A.P. Siva Kumar
language : en
Publisher: IIP Iterative International Publishers
Release Date : 2025-06-24
Exploring Data Science Concepts Techniques And Tools written by Dr. A.P. Siva Kumar and has been published by IIP Iterative International Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-24 with Computers categories.
Welcome to "Data Science with Python"! Whether you're a student, a professional looking to switch careers, or an enthusiast eager to explore the world of data science, this book is designed to take you on an exciting journey through one of the most rapidly growing fields in the world. Data science is the key to unlocking the potential of vast amounts of data in today's digital age. With Python emerging as the leading language for data analysis, machine learning, and visualization, this book leverages Python's rich ecosystem of libraries to provide a hands-on and practical approach to learning data science concepts. Throughout the chapters, you will gain a solid foundation in the essential techniques used in data science, including data manipulation, exploration, statistical analysis, machine learning, and data visualization. You’ll also find real-world examples, case studies, and step-by-step tutorials that will guide you in solving complex problems using Python. The book assumes no prior knowledge of data science or Python, making it suitable for beginners. As you progress, you will gradually move into more advanced topics, empowering you to build your own data-driven solutions with confidence. By the end of this book, you will not only have a deep understanding of the core principles of data science but also be equipped with practical skills to tackle real-world challenges using Python’s powerful data science tools. Whether you're analyzing business data, building machine learning models, or visualizing complex datasets, you'll find the skills you need to succeed. Data science is an ever-evolving field, and as you embark on this journey, remembers that learning is continuous. This book serves as a foundation for that journey, and the possibilities are endless as you dive deeper into data science with Python.
Analytics And Data Science
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Author : Amit V. Deokar
language : en
Publisher: Springer
Release Date : 2017-10-05
Analytics And Data Science written by Amit V. Deokar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-05 with Computers categories.
This book explores emerging research and pedagogy in analytics and data science that have become core to many businesses as they work to derive value from data. The chapters examine the role of analytics and data science to create, spread, develop and utilize analytics applications for practice. Selected chapters provide a good balance between discussing research advances and pedagogical tools in key topic areas in analytics and data science in a systematic manner. This book also focuses on several business applications of these emerging technologies in decision making, i.e., business analytics. The chapters in Analytics and Data Science: Advances in Research and Pedagogy are written by leading academics and practitioners that participated at the Business Analytics Congress 2015. Applications of analytics and data science technologies in various domains are still evolving. For instance, the explosive growth in big data and social media analytics requires examination of the impact of these technologies and applications on business and society. As organizations in various sectors formulate their IT strategies and investments, it is imperative to understand how various analytics and data science approaches contribute to the improvements in organizational information processing and decision making. Recent advances in computational capacities coupled by improvements in areas such as data warehousing, big data, analytics, semantics, predictive and descriptive analytics, visualization, and real-time analytics have particularly strong implications on the growth of analytics and data science.
Mastering Data Science A Comprehensive Guide To Techniques And Applications
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Author : Adam Jones
language : en
Publisher: Walzone Press
Release Date : 2025-01-05
Mastering Data Science A Comprehensive Guide To Techniques And Applications written by Adam Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-05 with Computers categories.
Embark on your data science journey with "Mastering Data Science: A Comprehensive Guide to Techniques and Applications," the ultimate resource for mastering the vast landscape of data science. Whether you're a novice eager to explore the field or an expert looking to refine and expand your skills, this book provides a thorough exploration of essential data science techniques and applications. Discover the foundational principles of data wrangling, preprocessing, statistical fundamentals, and essential mathematical techniques. Delve into the complexities of machine learning, deep learning, and natural language processing with clear explanations that connect theory to real-world practice. Each chapter is carefully designed to unravel complex concepts and features practical examples to enhance your understanding. Explore the intricacies of time series analysis, develop proficiency in crafting compelling data visualizations, and learn to effectively deploy machine learning models. With a focus on practical application, this guide not only imparts theoretical insights but also empowers you to address data science challenges confidently. Unlock the potential of data science to innovate, solve critical problems, and make informed decisions in today's data-centric world with "Mastering Data Science: A Comprehensive Guide to Techniques and Applications."
Biomedical Measurement Systems And Data Science
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Author : Michael Insana
language : en
Publisher: Cambridge University Press
Release Date : 2021-06-17
Biomedical Measurement Systems And Data Science written by Michael Insana and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-17 with Medical categories.
Discover the fundamental principles of biomedical measurement design and performance evaluation with this hands-on guide. Whether you develop measurement instruments or use them in novel ways, this practical text will prepare you to be an effective generator and consumer of biomedical data. Designed for both classroom instruction and self-study, it explains how information is encoded into recorded data and can be extracted and displayed in an accessible manner. Describes and integrates experimental design, performance assessment, classification, and system modelling. Combines mathematical concepts with computational models, providing the tools needed to answer advanced biomedical questions. Includes MATLAB® scripts throughout to help readers model all types of biomedical systems, and contains numerous homework problems, with a solutions manual available online. This is an essential text for advanced undergraduate and graduate students in bioengineering, electrical and computer engineering, computer science, medical physics, and anyone preparing for a career in biomedical sciences and engineering.