As data holdings get bigger and questions get harder, data scientists and analysts must focus on the systems, the tools and techniques, and the disciplined process to get the correct answer, quickly Whether you work within industry or government, this book will provide you with a foundation to successfully and confidently process large amounts of quantitative data.
Here are just a dozen of the many questions answered within these pages:
What does quantitative analysis of a system really mean?
What is a system?
What are big data and analystics?
How do you know your numbers are good?
What will the future data science environment look like?
How do you determine data provenance?
How do you gather and process information, and then organize, store, and synthesize it?
How does an organization implement data analytics?
Do you really need to think like a Chief Information Officer?
What is the best way to protect data?
What makes a good dashboard?
What is the relationship between eating ice cream and getting attacked by a shark?
The nine chapters in this book are arranged in three parts that address systems concepts in general, tools and techniques, and future trend topics. Systems concepts include contrasting open and closed systems, performing data mining and big data analysis, and gauging data quality. Tools and techniques include analyzing both continuous and discrete data, applying probability basics, and practicing quantitative analysis such as descriptive and inferential statistics. Future trends include leveraging the Internet of Everything, modeling Artificial Intelligence, and establishing a Data Analytics Support Office (DASO).
Many examples are included that were generated using common software, such as Excel, Minitab, Tableau, SAS, and Crystal Ball. While words are good, examples can sometimes be a better teaching tool. For each example included, data files can be found on the companion website. Many of the data sets are tied to the global economy because they use data from shipping ports, air freight hubs, largest cities, and soccer teams. The appendices contain more detailed analysis including the 10 T's for Data Mining, Million Row Data Audit (MRDA) Processes, Analysis of Rainfall, and Simulation Models for Evaluating Traffic Flow.
Описание: This proceedings constitutes the refereed post-conference proceedings of the 13th International Conference on Simulation Tools and Techniques, SIMUTools 2021, held in November 2021. Due to COVID-19 pandemic the conference was held virtually. The 63 revised full papers were carefully selected from 143 submissions. The papers focus on new results in the field of system modeling and simulation, software simulation, communication networks’ modeling and analysis, AI system simulation and performance analysis, big data simulation analysis, addressing current and future trends in simulation techniques. They are grouped in thematic aspects on wireless communication, big data, modeling and simulation, deep learning, network simulation and life and medical sciences.
Автор: Martin Arnold; Werner Schiehlen Название: Simulation Techniques for Applied Dynamics ISBN: 3211999469 ISBN-13(EAN): 9783211999462 Издательство: Springer Рейтинг: Цена: 24394.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume presents modeling and simulation techniques for the dynamical analysis of coupled engineering systems consisting of mechanical, electrical, hydraulic and biological components as well as control devices based on computer hardware and software.
Автор: Samui Pijush, Chakraborty Subrata, Kim Dookie Название: Modeling and Simulation Techniques in Structural Engineering ISBN: 1522505881 ISBN-13(EAN): 9781522505884 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 32017.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The development of new and effective analytical and numerical models is essential to understanding the performance of a variety of structures. As computational methods continue to advance, so too do their applications in structural performance modeling and analysis.Modeling and Simulation Techniques in Structural Engineering presents emerging research on computational techniques and applications within the field of structural engineering. This timely publication features practical applications as well as new research insights and is ideally designed for use by engineers, IT professionals, researchers, and graduate-level students.
Описание: Examines the latest scholarly research on the application of computational models to improve the quality of engineering design. This volume features extensive coverage of a range of topics from various engineering disciplines, including, but not limited to, soft computing methods, comparative studies, and hybrid approaches.
Описание: Computer simulations are the tools used to mathematically model natural systems in diverse fields of chemistry, astrophysics, biology, computational physics, social science, climatology, psychology, etc. They can be categorized into small simulations and large-scale simulations depending upon their usage. The different types of computer simulations are dynamic system simulation, stochastic or deterministic, local or distributed, and continuous or discrete simulations. Research in the field of computer simulation has extended its applications in the domains of weather forecasting, organizational management, traffic engineering, crop-soil systems, etc. This book is compiled in such a manner, that it will provide in-depth knowledge about the theory and development of computer simulation. It presents researches and studies performed by experts across the globe. Scientists and students actively engaged in this field will find this book full of crucial and unexplored concepts.
Автор: Yufeng Qian Название: Teaching, Learning, and Leading With Computer Simulations ISBN: 1799800059 ISBN-13(EAN): 9781799800057 Издательство: Mare Nostrum (Eurospan) Цена: 22037.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computer simulation, a powerful technological tool and research-proven pedagogical technique, holds great potential to enhance and transform teaching and learning in education and is therefore a viable tool to engage students in deep learning and higher-order thinking. With the advancement of simulation technology (e.g., virtual reality, artificial intelligence, machine learning) and the expanded disciplines where computer simulation is being used (e.g., data science, cyber security), computer simulation is playing an increasingly significant role in leading the digital transformation in K-12 schools and higher education institutions, as well as training and professional development in corporations, government, and the military. Teaching, Learning, and Leading With Computer Simulations is an important compilation of research that examines the recent advancement of simulation technology and explores innovative ways to utilize advanced simulation programs for the enhancement of teaching and learning outcomes. Highlighting a range of topics such as pedagogy, immersive learning, and social sciences, this book is essential for educators, higher education institutions, deans, curriculum designers, school administrators, principals, IT specialists, academicians, researchers, policymakers, and students.
Автор: Yufeng Qian Название: Teaching, Learning, and Leading With Computer Simulations ISBN: 1799800040 ISBN-13(EAN): 9781799800040 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 26195.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computer simulation, a powerful technological tool and research-proven pedagogical technique, holds great potential to enhance and transform teaching and learning in education and is therefore a viable tool to engage students in deep learning and higher-order thinking. With the advancement of simulation technology (e.g., virtual reality, artificial intelligence, machine learning) and the expanded disciplines where computer simulation is being used (e.g., data science, cyber security), computer simulation is playing an increasingly significant role in leading the digital transformation in K-12 schools and higher education institutions, as well as training and professional development in corporations, government, and the military.
Teaching, Learning, and Leading With Computer Simulations is an important compilation of research that examines the recent advancement of simulation technology and explores innovative ways to utilize advanced simulation programs for the enhancement of teaching and learning outcomes. Highlighting a range of topics such as pedagogy, immersive learning, and social sciences, this book is essential for educators, higher education institutions, deans, curriculum designers, school administrators, principals, IT specialists, academicians, researchers, policymakers, and students.
Описание: Introduction.- Simulation-Driven Design.- Fundamentals of Numerical Optimization.- Introduction to Surrogate-Based Modeling and Surrogate-Based Optimization.- Design Optimization Using Response Correction Techniques.- Surrogate-Based Optimization Using Parametric Response Correction.- Non-Parametric Response Correction Techniques.- Expedited Simulation-Driven Optimization Using Adaptively Adjusted Design Specification.- Surrogate-Assisted Design Optimization Using Response Features.- Enhancing Response Correction Techniques by Adjoint Sensitivity.- Multi-Objective Optimization Using Variable-Fidelity Models and Response Correction.- Physics-Base Surrogate Models Using Response Correction.- Summary and Discussion.- References.
Автор: Petr N. Vabishchevich Название: Computational Technologies: Advanced Topics ISBN: 3110359944 ISBN-13(EAN): 9783110359947 Издательство: Walter de Gruyter Цена: 9288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses questions of numerical solutions of applied problems on parallel computing systems. Nowadays, engineering and scientific computations are carried out on parallel computing systems, which provide parallel data processing on a few computing nodes. In the development of up-to-date applied software, this feature of computers must be taken into account for the maximum efficient usage of their resources. In constructing computational algorithms, we should separate relatively independent subproblems in order to solve them on a single computing node.
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