Foundations Of Data Science For Engineering Problem Solving
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Foundations Of Data Science For Engineering Problem Solving
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Author : Parikshit Narendra Mahalle
language : en
Publisher: Springer Nature
Release Date : 2021-08-21
Foundations Of Data Science For Engineering Problem Solving written by Parikshit Narendra Mahalle and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-21 with Technology & Engineering categories.
This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.
Recent Advancement In Geoinformatics And Data Science
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Author : Xiaogang Ma
language : en
Publisher: Geological Society of America
Release Date : 2023-04-11
Recent Advancement In Geoinformatics And Data Science written by Xiaogang Ma and has been published by Geological Society of America this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-11 with Science categories.
"The chapters in this Special Paper present the latest progress and discoveries in both the methodology and technology of geoinformatics. The methodologies, technologies, and best practices will make this volume a useful reference with long-term impacts for data-intensive geoscience in the next decade and beyond"--
Resources In Education
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Author :
language : en
Publisher:
Release Date : 1985-10
Resources In Education written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985-10 with Education categories.
Modern Data Science With R
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Author : Benjamin S. Baumer
language : en
Publisher: CRC Press
Release Date : 2021-04-13
Modern Data Science With R written by Benjamin S. Baumer and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-13 with Business & Economics categories.
From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.
Foundation Engineering
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Author : National Research Council (U.S.). Transportation Research Board
language : en
Publisher: Transportation Research Board National Research
Release Date : 1992
Foundation Engineering written by National Research Council (U.S.). Transportation Research Board and has been published by Transportation Research Board National Research this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Technology & Engineering categories.
Data Structures And Algorithms Using C
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Author : Dr. Kanika Singhal
language : en
Publisher: BFC Publications
Release Date : 2025-12-11
Data Structures And Algorithms Using C written by Dr. Kanika Singhal and has been published by BFC Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-11 with Education categories.
Data Structures Using C” is a comprehensive and student-friendly guide that lays a strong foundation for understanding how data is organized, managed, and processed in computer systems. Written with clarity and precision, the book systematically introduces core data structures such as arrays, stacks, queues, linked lists, trees, and graphs, along with essential algorithms for searching, sorting, and memory management. Each topic is explained through simple language, real-world examples, and well-structured C programs that demonstrate both logic and implementation. The book emphasizes a hands-on approach, enabling readers to strengthen their programming skills and develop problem solving abilities crucial for technical interviews, academic courses, and competitive exams. Special attention is given to how data structures operate internally and how different algorithms affect performance, helping students make intelligent choices while designing efficient programs. Practice questions, sample codes, and exercises at the end of each chapter make this book a complete learning resource for beginners as well as advanced learners. Whether you are a student of Computer Science, an aspiring software developer, or someone revising the fundamentals, “Data Structures Using C” will serve as your reliable companion in mastering the art of structured programming and algorithmic thinking.
Foundations Of Data Science
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Author : Avrim Blum
language : en
Publisher: Cambridge University Press
Release Date : 2020-01-23
Foundations Of Data Science written by Avrim Blum 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 2020-01-23 with Computers categories.
Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.
Resources In Education
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Author :
language : en
Publisher:
Release Date : 1996
Resources In Education written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Education categories.
Reverse Acronyms Initialisms Abbreviations Dictionary
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Author :
language : en
Publisher:
Release Date : 1985
Reverse Acronyms Initialisms Abbreviations Dictionary written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Abbreviations categories.
Data Science In Context
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Author : Alfred Z. Spector
language : en
Publisher: Cambridge University Press
Release Date : 2022-10-20
Data Science In Context written by Alfred Z. Spector 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 2022-10-20 with Computers categories.
Data science is the foundation of our modern world. It underlies applications used by billions of people every day, providing new tools, forms of entertainment, economic growth, and potential solutions to difficult, complex problems. These opportunities come with significant societal consequences, raising fundamental questions about issues such as data quality, fairness, privacy, and causation. In this book, four leading experts convey the excitement and promise of data science and examine the major challenges in gaining its benefits and mitigating its harms. They offer frameworks for critically evaluating the ingredients and the ethical considerations needed to apply data science productively, illustrated by extensive application examples. The authors' far-ranging exploration of these complex issues will stimulate data science practitioners and students, as well as humanists, social scientists, scientists, and policy makers, to study and debate how data science can be used more effectively and more ethically to better our world.