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Author: Satish Mahadevan Srinivasan
Publisher: CRC Press
ISBN: 100085969X
Category : Computers
Languages : en
Pages : 279
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Book Description
What Every Engineer Should Know About Data-Driven Analytics provides a comprehensive introduction to the theoretical concepts and approaches of machine learning that are used in predictive data analytics. By introducing the theory and by providing practical applications, this text can be understood by every engineering discipline. It offers a detailed and focused treatment of the important machine learning approaches and concepts that can be exploited to build models to enable decision making in different domains. Utilizes practical examples from different disciplines and sectors within engineering and other related technical areas to demonstrate how to go from data, to insight, and to decision making Introduces various approaches to build models that exploits different algorithms Discusses predictive models that can be built through machine learning and used to mine patterns from large datasets Explores the augmentation of technical and mathematical materials with explanatory worked examples Includes a glossary, self-assessments, and worked-out practice exercises Written to be accessible to non-experts in the subject, this comprehensive introductory text is suitable for students, professionals, and researchers in engineering and data science.
Author: Satish Mahadevan Srinivasan
Publisher: CRC Press
ISBN: 100085969X
Category : Computers
Languages : en
Pages : 279
Get Book Here
Book Description
What Every Engineer Should Know About Data-Driven Analytics provides a comprehensive introduction to the theoretical concepts and approaches of machine learning that are used in predictive data analytics. By introducing the theory and by providing practical applications, this text can be understood by every engineering discipline. It offers a detailed and focused treatment of the important machine learning approaches and concepts that can be exploited to build models to enable decision making in different domains. Utilizes practical examples from different disciplines and sectors within engineering and other related technical areas to demonstrate how to go from data, to insight, and to decision making Introduces various approaches to build models that exploits different algorithms Discusses predictive models that can be built through machine learning and used to mine patterns from large datasets Explores the augmentation of technical and mathematical materials with explanatory worked examples Includes a glossary, self-assessments, and worked-out practice exercises Written to be accessible to non-experts in the subject, this comprehensive introductory text is suitable for students, professionals, and researchers in engineering and data science.
Author: Satish Mahadevan Srinivasan
Publisher: CRC Press
ISBN: 100085972X
Category : Computers
Languages : en
Pages : 250
Get Book Here
Book Description
What Every Engineer Should Know About Data-Driven Analytics provides a comprehensive introduction to the theoretical concepts and approaches of machine learning that are used in predictive data analytics. By introducing the theory and by providing practical applications, this text can be understood by every engineering discipline. It offers a detailed and focused treatment of the important machine learning approaches and concepts that can be exploited to build models to enable decision making in different domains. Utilizes practical examples from different disciplines and sectors within engineering and other related technical areas to demonstrate how to go from data, to insight, and to decision making Introduces various approaches to build models that exploits different algorithms Discusses predictive models that can be built through machine learning and used to mine patterns from large datasets Explores the augmentation of technical and mathematical materials with explanatory worked examples Includes a glossary, self-assessments, and worked-out practice exercises Written to be accessible to non-experts in the subject, this comprehensive introductory text is suitable for students, professionals, and researchers in engineering and data science.
Author: Piyanka Jain
Publisher: AMACOM
ISBN: 0814449220
Category : Business & Economics
Languages : en
Pages : 276
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Book Description
There is a misconception in business that the only data that matters is BIG data, and that elaborate tools and data scientists are required to extract any practical information. However, nothing could be further from the truth. If you feel that you can’t understand how to read, let alone implement, these complex software programs that crunch the data and spit out more data, that will no longer be a problem! Authors and analytics experts Piyanka Jain and Puneet Sharma demystify the process of business analytics and demonstrate how professionals at any level can take the information at their disposal and in only five simple steps--using only Excel as a tool--make the decision necessary to increase revenue, decrease costs, improve product, or whatever else is being asked of them at that time. In Behind Every Good Decision, you will learn how to: Clarify the business question Lay out a hypothesis-driven plan Pull relevant data Convert it to insights Make decisions that make an impact Packed with examples and exercises, this refreshingly accessible book explains the four fundamental analytic techniques that can help solve a surprising 80 percent of all business problems. It doesn’t take a numbers person to know that is a formula you need!
Author: Sarah Horton
Publisher: CRC Press
ISBN: 1040009832
Category : Business & Economics
Languages : en
Pages : 258
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Book Description
Accessibility is a core quality of digital products to be deliberately addressed throughout the development lifecycle. What Every Engineer Should Know About Digital Accessibility will prepare readers to integrate digital accessibility into their engineering practices. Readers will learn how to accurately frame accessibility as an engineering challenge so they are able to address the correct problems in the correct way. Illustrated with diverse perspectives from accessibility practitioners and advocates, this book describes how people with disabilities use technology, the nature of accessibility barriers in the digital world, and the role of engineers in breaking down those barriers. Accessibility competence for current, emerging, and future technologies is addressed through a combination of guiding principles, core attributes and requirements, and accessibility‐informed engineering practices. FEATURES Discusses how technology can support inclusion for people with disabilities and how rigorous engineering processes help create quality user experiences without introducing accessibility barriers Explains foundational principles and guidelines that build core competency in digital accessibility as they are applied across diverse and emerging technology platforms Highlights practical insights into how engineering teams can effectively address accessibility throughout the technology development lifecycle Uses international standards to define and measure accessibility quality Written to be accessible to non‐experts in the subject area, What Every Engineer Should Know About Digital Accessibility is aimed at students, professionals, and researchers in the field of software engineering.
Author: Valdemar Vicente Graciano Neto
Publisher: CRC Press
ISBN: 1000959163
Category : Technology & Engineering
Languages : en
Pages : 289
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Book Description
Get ready to be at the forefront of the future of urban development! As cities continue to rapidly grow, the demand for sustainable and efficient infrastructure becomes more urgent. That’s where What Every Engineer Should Know About Smart Cities comes in, offering a comprehensive guide to the concepts and technologies driving the transformation of our cities. Delve into the world of smart cities and discover how information and communication technologies are revolutionizing urban environments. With clear definitions and a focus on real-world applications, this book explores the benefits and challenges of smart cities. It also highlights interdisciplinary topics such as smart buildings, autonomous cars, and urban emergency management systems. This book is not just a theoretical exploration of smart cities. It goes beyond that by providing an in-depth look at the key technologies that are essential to creating smart cities. From the Internet of Things and blockchain to digital twins and modeling and simulations, readers will gain a solid understanding of the foundational technologies that make smart cities possible. With detailed discussions and real-world examples of smart mobility, smart health, smart education, and smart agribusiness, readers will gain a deep understanding of the requirements and characteristics that engineers need to contribute to the development of smart cities. Whether you’re an engineer looking to expand your knowledge, a city planner seeking to understand the latest trends, or simply someone interested in the future of urban living, What Every Engineer Should Know About Smart Cities is the ultimate guide to unlocking the potential of smart cities for sustainable urban development and improved quality of life.
Author: Steven L. Brunton
Publisher: Cambridge University Press
ISBN: 1009098489
Category : Computers
Languages : en
Pages : 615
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Book Description
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Author: Mohammad Modarres
Publisher: CRC Press
ISBN: 1000864103
Category : Technology & Engineering
Languages : en
Pages : 481
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Book Description
Emphasises an introduction and explanation of the practical methods used in reliability, and risk studies with a discussion of their uses and limitations Offers basic and advanced methods in reliability analysis that are commonly used in daily practice Provides methods that address unique topics such as dependent failure analysis, importance analysis, and analysis of repairable systems Presents a comprehensive overview of modern probabilistic life assessment methods such as Bayesian estimation, system reliability analysis, and human reliability Includes many ends of chapter problems, a tools website with computational codes, along with a solutions manual to support course adoptions
Author: Eugene Schlossberger
Publisher: CRC Press
ISBN: 1000849546
Category : Technology & Engineering
Languages : en
Pages : 362
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Book Description
Ethical Engineering: A Practical Guide with Case Studies provides detailed and practical guidance in making decisions about the many ethical issues practicing engineers may face in their professional lives. It outlines a decision-making procedure and helps engineers construct an ethics toolkit consisting of professional models, a comprehensive set of ethical considerations and factors that help in weighing those considerations, and analyses of particular issues, such as reverse engineering a patented process. Illustrating case studies, both brief and detailed, are provided. Features: • Introduces the nature of ethical decision-making as applied to engineering values and issues. • Helps readers develop a detailed ethics toolkit that identifies options and solutions and allows them to monitor and adjust as necessary. • Features topics such as safety, sustainability, bioethics, diversity and equality, information technology and AI, as well as critical areas often overlooked in engineering texts, such as mentoring, advertising (for consulting firms), engineering sales, and much more. • Includes 85 case studies to illustrate a variety of scenarios. • Offers an international perspective with codes of ethics from around the world, including Saudi Arabia, India, New Zealand, Chile, and Japan. Emphasizing the importance of the moral life and of engineering as an occupation with high ideals, this book helps readers navigate a variety of real-world ethical issues they are likely to face in this increasingly interdisciplinary, global, and diverse profession.
Author: Joanna F. DeFranco
Publisher: CRC Press
ISBN: 1000473724
Category : Computers
Languages : en
Pages : 217
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Book Description
Internet of Things (IoT) products and cyber-physical systems (CPS) are being utilized in almost every discipline and there continues to be significant increases in spending on design, development, and deployment of IoT applications and analytics within every domain, from our homes, schools, government, and industry. This practical text provides an introduction to IoT that can be understood by every engineering discipline and discusses detailed applications of IoT. Developed to help engineers navigate this increasingly important and cross-disciplinary topic, this work: Offers research-based examples and case studies to facilitate the understanding of each IoT primitive Highlights IoT’s connection to blockchain Provides and understanding of benefits and challenges of IoT and its importance to a variety of engineering disciplines Written to be accessible to non-experts in the subject, What Every Engineer Should Know About the Internet of Things communicates the importance of this technology and how it can support and challenge all interrelated actors as well as all involved assets across many domains.
Author: Parul Gandhi
Publisher: CRC Press
ISBN: 9781032058283
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
This book aims to explain Data Analytics towards decision making in terms of models and algorithms, theoretical concepts, applications, experiments in relevant domains or focused on specific issues. It explores the concepts of database technology, machine learning, knowledge-based system, high performance computing, information retrieval, finding patterns hidden in large datasets and data visualization. Also, it presents various paradigms including pattern mining, clustering, classification, and data analysis. Overall aim is to provide technical solutions in the field of data analytics and data mining. Features: Covers descriptive statistics with respect to predictive analytics and business analytics. Discusses different data analytics platforms for real-time applications. Explain SMART business models. Includes algorithms in data sciences alongwith automated methods and models. Explores varied challenges encountered by researchers and businesses in the realm of real-time analytics. This book aims at researchers and graduate students in data analytics, data sciences, data mining, and signal processing.
