Machine Learning for Financial Risk Management with Python

Using the lens of history, A History of Financial Technology and Regulation illuminates recent changes to the world of finance. With lucid prose and the help of concrete examples, Seth Oranburg helps readers understand the role of technology in finance today, including complex phenomena such as mutual funds, cryptocurrencies, and the stock market itself. Chapters begin with basic principles and historical analogy before describing complex digital-investment strategies and instruments. Readers will also gain an introduction to key concepts in financial regulation, learning how law and regulations prevented some financial crises while perpetuating others. Oranburg concludes with ideas about what's next for finance and how the law should respond. This book will appeal to specialists and nonspecialists alike who are interesting in learning more about business, economics, finance, law, and regulation.

This accessible book explores the development of play skills and schemas to support children with learning differences and physical disabilities in learning to play.Each chapter looks at an aspect of play - from play therapy and sensory play, to LEGO, role play and digital play - and discusses how the approach can meet the needs of children in specialist settings, from those with sensory needs, to children with physical disabilities. The book introduces a myriad of different ways to use play and shares both evidence and anecdotes of the benefits to physical and mental health, as well as learning. Rich examples are given from special schools who have intentionally designed their schools to meet the play needs of their children and a range of adaptable resources are also provided, including policy documents and risk assessments ready to be taken away and used. Learning Through Play in Special Education will be essential reading for teachers working with children with additional needs and

Deep learning on graphs has become one of the hottest topics in machine learning. The book consists of four parts to best accommodate our readers with diverse backgrounds and purposes of reading. Part 1 introduces basic concepts of graphs and deep learning; Part 2 discusses the most established methods from the basic to advanced settings; Part 3 presents the most typical applications including natural language processing, computer vision, data mining, biochemistry and healthcare; and Part 4 describes advances of methods and applications that tend to be important and promising for future research. The book is self-contained, making it accessible to a broader range of readers including (1) senior undergraduate and graduate students; (2) practitioners and project managers who want to adopt graph neural networks into their products and platforms; and (3) researchers without a computer science background who want to use graph neural networks to advance their disciplines.

Global and national confidential inquiry reports show that 60 to 80% of maternal and neonatal morbidity and mortality are due to avoidable errors. This comprehensive and illustrated second edition offers a practical guide to the management of obstetric, medical, surgical, anaesthetic and newborn emergencies in addition to organisational and training issues. The book is divided conveniently into nine sections and updated throughout in line with modern research and practice. Several new chapters cover setting up skills and drills training in maternity services to reduce avoidable harm, managing obstetric emergencies during 'home births' and in low-risk midwifery units, and minimizing maternal and fetal morbidity in failed operative vaginal delivery. Each chapter includes a practical algorithm for quick reference, the scientific basis for proposed actions, a case-based practical exercise and useful learning tools such as 'Key Pearls' and 'Key Pitfalls'. An invaluable resource for obstetri

Bears have fascinated people since ancient times. The relationship between bears and humans dates back thousands of years, during which time we have also competed with bears for shelter and food. In modern times, bears have come under pressure through encroachment on their habitats, climate change, and illegal trade in their body parts, including the Asian bear bile market. The IUCN lists six bears as vulnerable or endangered, and even the least concern species, such as the brown bear, are at risk of extirpation in certain countries. The poaching and international trade of these most threatened populations are prohibited, but still ongoing. Covering all bears species worldwide, this beautifully illustrated volume brings together the contributions of 200 international bear experts on the ecology, conservation status, and management of the Ursidae family. It reveals the fascinating long history of interactions between humans and bears and the threats affecting these charismatic species.

Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This introduction for researchers and graduate students is the first in-depth, comprehensive treatment of statistical and machine learning methods for neuroscience. The methods are demonstrated through case studies of real problems to empower readers to build their own solutions. The book covers a wide variety of methods, including supervised classification with non-probabilistic models (nearest-neighbors, classification trees, rule induction, artificial neural networks and support vector machines) and probabilistic models (discriminant analysis, logistic regression and Bayesian network classifiers), meta-classifiers, multi-dimensional classifiers and feature subset selection methods. Other parts of the book are devoted to association discovery with probabilistic graphical models (Bayesian networks and Markov networks) and spatial statistics with po

Calling for the transformation of undergraduate education, Thomas and Harney argue that the liberal arts should be integrated into the traditional management curriculum to blend technical and analytic acumen with creativity, critical thinking, and ethical intelligence. In describing their vision for a new liberal management education, the authors demonstrate how a holistic pedagogy that does not sacrifice one wealth of learning for another instead encourages participation and integration to the benefit of students and society. Global in sweep, the book provides case studies of successfully implemented experimental courses in Asia and Britain, as well as a speculative chapter on how an African liberal management education could take shape, based on African-centred principles and histories. Finally, the book argues that the stakes of this agenda go beyond mere curricular reform and pedagogical innovation and speak directly to the environmental, business, political, and social challenges

This beloved and market-leading Operations Management book has been completely updated in the 14th edition and provides a clear presentation of the field of Operations Management with current real-world examples and thoughtful student pedagogy. The comprehensive breadth of content is presented in more modular flexible chapters, so it may be used for different course levels ranging from undergrad to executive education. That flexibility allows for the choice of more or less quantitative material and flexibility in order of presentation since chapters do not depend on sequence.The topics covered include both strategic issues and practical applications. Among the topics are forecasting, product and service design, capacity planning, management of quality and quality control, inventory management, scheduling, supply chain management, and project management. The use of an adaptive online learning enhances the student experience and success.

Both a serious academic text and an intriguing story, this seventh edition reflects a significant update in research, theory, and applications in all areas. It presents a comprehensive view of the historical development of learning theories from behaviorist through to cognitive models. The chapters also cover memory, motivation, social learning, machine learning, and artificial intelligence. The author's highly entertaining style clarifies concepts, emphasizes practical applications, and presents a thought-provoking, narrator-based commentary. The stage is given to Mrs Gribbin and her swashbuckling cat, who both lighten things up and supply much-needed detail. These two help to explore the importance of technology for simulating human cognitive processes and engage with current models of memory. They investigate developments in, and applications of, brain-based research and plunge into models in motivation theory, to name but a few of the adventures they embark upon in this textbook.

Both a serious academic text and an intriguing story, this seventh edition reflects a significant update in research, theory, and applications in all areas. It presents a comprehensive view of the historical development of learning theories from behaviorist through to cognitive models. The chapters also cover memory, motivation, social learning, machine learning, and artificial intelligence. The author's highly entertaining style clarifies concepts, emphasizes practical applications, and presents a thought-provoking, narrator-based commentary. The stage is given to Mrs Gribbin and her swashbuckling cat, who both lighten things up and supply much-needed detail. These two help to explore the importance of technology for simulating human cognitive processes and engage with current models of memory. They investigate developments in, and applications of, brain-based research and plunge into models in motivation theory, to name but a few of the adventures they embark upon in this textbook.

A Great Deal of Ruin provides an accessible introduction to the enduring problem of financial crises. Illustrated with historical analysis, case studies, and clear economic concepts, this book explains in three parts what financial crises are, how they are caused and what we can learn from them. It begins with a taxonomy of crises and a list of factors that increase the risk for countries experiencing a financial crisis. It then examines five of the most important crises in modern economic history, beginning with the Great Depression and ending with the subprime crisis in the United States and its evolution into a debt crisis in the Eurozone. The book concludes with a set of lessons that can be learnt from the crises of the past. It will appeal to university students as well as general readers who are curious to learn more about the recent subprime crisis and other financial crises.

A Great Deal of Ruin provides an accessible introduction to the enduring problem of financial crises. Illustrated with historical analysis, case studies, and clear economic concepts, this book explains in three parts what financial crises are, how they are caused and what we can learn from them. It begins with a taxonomy of crises and a list of factors that increase the risk for countries experiencing a financial crisis. It then examines five of the most important crises in modern economic history, beginning with the Great Depression and ending with the subprime crisis in the United States and its evolution into a debt crisis in the Eurozone. The book concludes with a set of lessons that can be learnt from the crises of the past. It will appeal to university students as well as general readers who are curious to learn more about the recent subprime crisis and other financial crises.

Variational Bayesian learning is one of the most popular methods in machine learning. Designed for researchers and graduate students in machine learning, this book summarizes recent developments in the non-asymptotic and asymptotic theory of variational Bayesian learning and suggests how this theory can be applied in practice. The authors begin by developing a basic framework with a focus on conjugacy, which enables the reader to derive tractable algorithms. Next, it summarizes non-asymptotic theory, which, although limited in application to bilinear models, precisely describes the behavior of the variational Bayesian solution and reveals its sparsity inducing mechanism. Finally, the text summarizes asymptotic theory, which reveals phase transition phenomena depending on the prior setting, thus providing suggestions on how to set hyperparameters for particular purposes. Detailed derivations allow readers to follow along without prior knowledge of the mathematical techniques specific to

Effective leadership is critical to ensuring safety, efficiency and maximum productivity in the operating room (OR). This practical, evidence-based book unpicks the dynamics of a successful OR environment to underline the key techniques for management of policies, systems, staff members and teams. Fully updated to include recent clinical guidelines, the book provides the 'A-Z' of OR management, including sections on metrics, scheduling, human resource management, leadership principles, economics, quality assurance, recovery and ambulatory practice. New chapters include future healthcare models, emergency preparedness and budgets amongst other topics. Written by authors with unrivalled experience in the field, chapters are laid out in an easy and clinically helpful format to assist learning, and real-life case studies cover seventy-three different clinically relevant pain topics. This book is an essential guide for anyone working in the OR including anaesthesiologists, surgeons, nurses,

This book provides detailed information on the different forms of injury that are associated with training for and participation in Alpine skiing, covering risk factors and epidemiology, incidence, in