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Fundamentals of Machine Learning - Thomas P. (professor Of Computer Science Trappenberg - Bog - Oxford University Press - Plusbog.dk

Fundamentals of Machine Learning - Thomas P. (professor Of Computer Science Trappenberg - Bog - Oxford University Press - Plusbog.dk

Interest in machine learning is exploding worldwide, both in research and for industrial applications. Machine learning is fast becoming a fundamental part of everyday life. This book is a brief introduction to this area - exploring its importance in a range of many disciplines, from science to engineering, and even its broader impact on our society. The book is written in a style that strikes a balance between brevity of explanation, rigorous mathematical argument, and outlines principle ideas. At the same time, it provides a comprehensive overview of a variety of methods and their application within this field. This includes an introduction to Bayesian approaches to modeling, as well as deep learning. Writing small programs to apply machine learning techniques is made easy by high level programming systems, and this book shows examples in Python with the machine learning libraries ''sklearn'' and ''Keras''. The first four chapters concentrate on the practical side of applying machine learning techniques. The following four chapters discuss more fundamental concepts that includes their formulation in a probabilistic context. This is followed by two more chapters on advanced models, that of recurrent neural networks and that of reinforcement learning. The book closes with a brief discussion on the impact of machine learning and AI on our society.Fundamentals of Machine Learning provides a brief and accessible introduction to this rapidly growing field, one that will appeal to students and researchers across computer science and computational neuroscience, as well as the broader cognitive sciences.

DKK 464.00
3

Machine Learning for Econometrics - Christophe Gaillac - Bog - Oxford University Press - Plusbog.dk

Machine Learning for Econometrics - Christophe Gaillac - Bog - Oxford University Press - Plusbog.dk

Machine Learning for Econometrics is a book for economists seeking to grasp modern machine learning techniques - from their predictive performance to the revolutionary handling of unstructured data - in order to establish causal relationships from data. The volume covers automatic variable selection in various high-dimensional contexts, estimation of treatment effect heterogeneity, natural language processing (NLP) techniques, as well as synthetic control and macroeconomic forecasting. The foundations of machine learning methods are introduced to provide both a thorough theoretical treatment of how they can be used in econometrics and numerous economic applications, and each chapter contains a series of empirical examples, programs, and exercises to facilitate the reader''s adoption and implementation of the techniques.

DKK 416.00
2

Machine Learning for Econometrics - Christophe Gaillac - Bog - Oxford University Press - Plusbog.dk

Machine Learning for Econometrics - Christophe Gaillac - Bog - Oxford University Press - Plusbog.dk

Machine Learning for Econometrics is a book for economists seeking to grasp modern machine learning techniques - from their predictive performance to the revolutionary handling of unstructured data - in order to establish causal relationships from data. The volume covers automatic variable selection in various high-dimensional contexts, estimation of treatment effect heterogeneity, natural language processing (NLP) techniques, as well as synthetic control and macroeconomic forecasting. The foundations of machine learning methods are introduced to provide both a thorough theoretical treatment of how they can be used in econometrics and numerous economic applications, and each chapter contains a series of empirical examples, programs, and exercises to facilitate the reader''s adoption and implementation of the techniques.

DKK 1177.00
2

Demystifying China's Innovation Machine - Marina Zhang - Bog - Oxford University Press - Booktok.dk

Demystifying China's Innovation Machine - Marina Zhang - Bog - Oxford University Press - Booktok.dk

China''s extraordinary economic development is explained in large part by the way it innovates. Contrary to widely held views, China''s innovation machine is not created and controlled by an all-powerful government. Instead, it is a complex, interdependent system composed of various elements, involving bottom-up innovation driven by innovators and entrepreneurs and highly pragmatic and adaptive top-down policy. Using case studies of leading firms and industries, along with statistics and policy analysis, this book argues that China''s innovation machine is similar to a natural ecosystem. Innovations in technology, organization, and business models resemble genetic mutations which are initially random, self-serving, and isolated, but the best fitting are selected by the market and their impacts are amplified by the innovation machine. This machine draws on China''s multitude manufacturers, supply chains, innovation clusters, and digitally literate population, connected through super-sized digital platforms. China''s innovation suffers from a lack of basic research and reliance upon certain critical technologies from overseas, yet its scale (size) and scope (diversity) possess attributes that make it self-correcting and stronger in the face of challenges. China''s innovation machine is most effective in a policy environment where the market prevails; policy intervention plays a significant role when market mechanisms are premature or fail. The future success of China''s innovation will depend on continuing policy pragmatism, mass innovation, and entrepreneurship, and the development of the ''new infrastructures''.

DKK 517.00
4