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| blazingly fast math help: Math Tools Georg Glaeser, 2017-09-13 In this book, topics such as algebra, trigonometry, calculus and statistics are brought to life through over 500 applications ranging from biology, physics and chemistry to astronomy, geography and music. With over 600 illustrations emphasizing the beauty of mathematics, Math Tools complements more theoretical textbooks on the market, bringing the subject closer to the reader and providing a useful reference to students. By highlighting the ubiquity of mathematics in practical fields, the book will appeal not only to students and teachers, but to anyone with a keen interest in mathematics and its applications. |
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| blazingly fast math help: Mitonuclear Ecology Geoffrey E. Hill, 2019-04-30 This novel text provides a concise synthesis of how the interactions between mitochondrial and nuclear genes have played a major role in shaping the ecology and evolution of eukaryotes. The foundation for this new focus on mitonuclear interactions originated from research in biochemistry and cell biology laboratories, although the broader ecological and evolutionary implications have yet to be fully explored. The imperative for mitonuclear coadaptation is proposed to be a major selective force in the evolution of sexual reproduction and two mating types in eukaryotes, in the formation of species, in the evolution of ornaments and sexual selection, in the process of adaptation, and in the evolution of senescence. The book highlights the importance of mitonuclear coadaptation to the evolution of complex life and champions mitonuclear ecology as an important subdiscipline in ecology and evolution. |
| blazingly fast math help: Federated Learning with Python Kiyoshi Nakayama PhD, George Jeno, 2022-10-28 Learn the essential skills for building an authentic federated learning system with Python and take your machine learning applications to the next level Key FeaturesDesign distributed systems that can be applied to real-world federated learning applications at scaleDiscover multiple aggregation schemes applicable to various ML settings and applicationsDevelop a federated learning system that can be tested in distributed machine learning settingsBook Description Federated learning (FL) is a paradigm-shifting technology in AI that enables and accelerates machine learning (ML), allowing you to work on private data. It has become a must-have solution for most enterprise industries, making it a critical part of your learning journey. This book helps you get to grips with the building blocks of FL and how the systems work and interact with each other using solid coding examples. FL is more than just aggregating collected ML models and bringing them back to the distributed agents. This book teaches you about all the essential basics of FL and shows you how to design distributed systems and learning mechanisms carefully so as to synchronize the dispersed learning processes and synthesize the locally trained ML models in a consistent manner. This way, you'll be able to create a sustainable and resilient FL system that can constantly function in real-world operations. This book goes further than simply outlining FL's conceptual framework or theory, as is the case with the majority of research-related literature. By the end of this book, you'll have an in-depth understanding of the FL system design and implementation basics and be able to create an FL system and applications that can be deployed to various local and cloud environments. What you will learnDiscover the challenges related to centralized big data ML that we currently face along with their solutionsUnderstand the theoretical and conceptual basics of FLAcquire design and architecting skills to build an FL systemExplore the actual implementation of FL servers and clientsFind out how to integrate FL into your own ML applicationUnderstand various aggregation mechanisms for diverse ML scenariosDiscover popular use cases and future trends in FLWho this book is for This book is for machine learning engineers, data scientists, and artificial intelligence (AI) enthusiasts who want to learn about creating machine learning applications empowered by federated learning. You'll need basic knowledge of Python programming and machine learning concepts to get started with this book. |
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| blazingly fast math help: Information Systems Security Vallipuram Muthukkumarasamy, Sithu D. Sudarsan, Rudrapatna K. Shyamasundar, 2023-12-08 This book constitutes the refereed proceedings of the19th International Conference on Information Systems Security, ICISS 2023, held in Raipur, India, during December 16–20, 2023. The 18 full papers and 10 short papers included in this book were carefully reviewed and selected from 78 submissions. They are organized in topical sections as follows: systems security, network security, security in AI/ML, privacy, cryptography, blockchains. |
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| blazingly fast math help: Modeling Risk Johnathan Mun, 2010-06-15 An updated guide to risk analysis and modeling Although risk was once seen as something that was both unpredictable and uncontrollable, the evolution of risk analysis tools and theories has changed the way we look at this important business element. In the Second Edition of Analyzing and Modeling Risk, expert Dr. Johnathan Mun provides up-to-date coverage of risk analysis as it is applied within the realms of business risk analysis and offers an intuitive feel of what risk looks like, as well as the different ways of quantifying it. This Second Edition provides professionals in all industries a more comprehensive guide on such key concepts as risk and return, the fundamentals of model building, Monte Carlo simulation, forecasting, time-series and regression analysis, optimization, real options, and more. Includes new examples, questions, and exercises as well as updates using Excel 2007 Book supported by author's proprietary risk analysis software found on the companion CD-ROM Offers both a qualitative and quantitative description of risk Filled with in-depth insights and practical advice, this reliable resource covers all of the essential tools and techniques that risk managers need to successfully conduct risk analysis. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file. |
| blazingly fast math help: PC Mag , 1994-05-31 PCMag.com is a leading authority on technology, delivering Labs-based, independent reviews of the latest products and services. Our expert industry analysis and practical solutions help you make better buying decisions and get more from technology. |
| blazingly fast math help: InfoWorld , 1987-10-12 InfoWorld is targeted to Senior IT professionals. Content is segmented into Channels and Topic Centers. InfoWorld also celebrates people, companies, and projects. |
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| blazingly fast math help: Scholar of Magic Michael G. Manning, 2020-04-27 The looming war with Darrow has faded to a distant shadow, but Will’s continued studies at Wurthaven are disrupted by an unforeseen threat. Selene’s absence has raised suspicion among her friends and Will’s father-in-law, the king, who is now directing his ire at the obvious culprit, his daughter’s new husband. Meanwhile the citizens of Cerria have begun disappearing and a shadowy figure is stalking Will’s sister, Laina. With his power pushed to the limit, Will finds himself attempting to preserve a family that rejected him and trying to save a city whose king might rather see him dead. Desperate for help, he may not be able to trust the powers that have supported him in the past, for though the fae could be the source of the catastrophe; they only offer their assistance—for a price. Evil stalks the streets of Cerria at night, seeking the blood of his family, the destruction of the city, and the death of the king. Will may have to decide what is most important for Terabinia: preserving the people of its most prosperous city, or saving its questionable ruler? |
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| blazingly fast math help: Baseball's Other All-Stars William F. McNeil, 2000-03-01 Baseball is played in all corners of the world, so it is no surprise to learn that some of the greatest hardballers of all time never played on a U.S. major league diamond. Who knows what major league records would have been shattered had Sadaharu Oh of Japan, Josh Gibson of the Negro Leagues, Martin Dihigo of Cuba, Francisco Coimbre of Puerto Rico and Hector Espino of Mexico played in the United States. This work is a survey of the greatest baseball players who never played in the U.S. major leagues. The greatest players from the various professional leagues outside organized baseball in the United States are reviewed, and all-star teams are selected for each league. Finally, the author selects an all-world all-star team from the individual all-star teams from Japan, Mexico, Cuba, Puerto Rico, the Dominican Republic and the Negro Leagues. |
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| blazingly fast math help: The Math Teachers Know Brent Davis, Moshe Renert, 2013-07-18 What sorts of mathematics competencies must teachers have in order to teach the discipline well? This book offers a novel take on the question. Most research is focused on explicit knowledge–that is, on the sorts of insights that might be specified, catalogued, taught, and tested. In contrast, this book focuses on the tacit dimensions of teachers’ mathematics knowledge that precede and enable their competencies with formal mathematics. It highlights the complexity of this knowledge and offers strategies to uncover it, analyze it, and re-synthesize it in ways that will make it more available for teaching. Emerging from 10 years of collaborative inquiry with practicing teachers, it is simultaneously informed by the most recent research and anchored to the realities of teachers’ lives in classrooms. |
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| blazingly fast math help: Evolutionary Computation David B. Fogel, 2006-01-03 This Third Edition provides the latest tools and techniques that enable computers to learn The Third Edition of this internationally acclaimed publication provides the latest theory and techniques for using simulated evolution to achieve machine intelligence. As a leading advocate for evolutionary computation, the author has successfully challenged the traditional notion of artificial intelligence, which essentially programs human knowledge fact by fact, but does not have the capacity to learn or adapt as evolutionary computation does. Readers gain an understanding of the history of evolutionary computation, which provides a foundation for the author's thorough presentation of the latest theories shaping current research. Balancing theory with practice, the author provides readers with the skills they need to apply evolutionary algorithms that can solve many of today's intransigent problems by adapting to new challenges and learning from experience. Several examples are provided that demonstrate how these evolutionary algorithms learn to solve problems. In particular, the author provides a detailed example of how an algorithm is used to evolve strategies for playing chess and checkers. As readers progress through the publication, they gain an increasing appreciation and understanding of the relationship between learning and intelligence. Readers familiar with the previous editions will discover much new and revised material that brings the publication thoroughly up to date with the latest research, including the latest theories and empirical properties of evolutionary computation. The Third Edition also features new knowledge-building aids. Readers will find a host of new and revised examples. New questions at the end of each chapter enable readers to test their knowledge. Intriguing assignments that prepare readers to manage challenges in industry and research have been added to the end of each chapter as well. This is a must-have reference for professionals in computer and electrical engineering; it provides them with the very latest techniques and applications in machine intelligence. With its question sets and assignments, the publication is also recommended as a graduate-level textbook. |
| blazingly fast math help: InfoWorld , 1988-11-14 InfoWorld is targeted to Senior IT professionals. Content is segmented into Channels and Topic Centers. InfoWorld also celebrates people, companies, and projects. |
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