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

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

Demystifying China's Innovation Machine - David Gann - Bog - Oxford University Press - Plusbog.dk

Demystifying China's Innovation Machine - David Gann - Bog - Oxford University Press - Plusbog.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 545.00
1

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 440.00
1

The Universal Turing Machine - - Bog - Oxford University Press - Plusbog.dk

Oxford Read and Imagine: Level 4:: A Machine for the Future - Paul Shipton - Bog - Oxford University Press - Plusbog.dk

Machine Learning for Signal Processing - Prof Max A. Little - Bog - Oxford University Press - Plusbog.dk

Machine Learning for Signal Processing - Prof Max A. Little - Bog - Oxford University Press - Plusbog.dk

This book describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Taking a gradual approach, it builds up concepts in a solid, step-by-step fashion so that the ideas and algorithms can be implemented in practical software applications.Digital signal processing (DSP) is one of the ''foundational'' engineering topics of the modern world, without which technologies such the mobile phone, television, CD and MP3 players, WiFi and radar, would not be possible. A relative newcomer by comparison, statistical machine learning is the theoretical backbone of exciting technologies such as automatic techniques for car registration plate recognition, speech recognition, stock market prediction, defect detection on assembly lines, robot guidance, and autonomous car navigation. Statistical machine learning exploits the analogy between intelligent information processing in biological brains and sophisticated statistical modelling and inference.DSP and statistical machine learning are of such wide importance to the knowledge economy that both have undergone rapid changes and seen radical improvements in scope and applicability. Both make use of key topics in applied mathematics such as probability and statistics, algebra, calculus, graphs and networks. Intimate formal links between the two subjects exist and because of this many overlaps exist between the two subjects that can be exploited to produce new DSP tools of surprising utility, highly suited to the contemporary world of pervasive digital sensors and high-powered, yet cheap, computing hardware. This book gives a solid mathematical foundation to, and details the key concepts and algorithms in this important topic.

DKK 382.00
1

Oxford Reading Tree TreeTops Fiction: Level 12 More Pack C: Scrapman and the Incredible Flying Machine - Carolyn Bear - Bog - Oxford University Press

Machine Learning for Signal Processing - Max A. (professor Of Mathematics Little - Bog - Oxford University Press - Plusbog.dk

Machine Learning for Signal Processing - Max A. (professor Of Mathematics Little - Bog - Oxford University Press - Plusbog.dk

This book describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Taking a gradual approach, it builds up concepts in a solid, step-by-step fashion so that the ideas and algorithms can be implemented in practical software applications. Digital signal processing (DSP) is one of the ''foundational'' engineering topics of the modern world, without which technologies such the mobile phone, television, CD and MP3 players, WiFi and radar, would not be possible. A relative newcomer by comparison, statistical machine learning is the theoretical backbone of exciting technologies such as automatic techniques for car registration plate recognition, speech recognition, stock market prediction, defect detection on assembly lines, robot guidance, and autonomous car navigation. Statistical machine learning exploits the analogy between intelligent information processing in biological brains and sophisticated statistical modelling and inference. DSP and statistical machine learning are of such wide importance to the knowledge economy that both have undergone rapid changes and seen radical improvements in scope and applicability. Both make use of key topics in applied mathematics such as probability and statistics, algebra, calculus, graphs and networks. Intimate formal links between the two subjects exist and because of this many overlaps exist between the two subjects that can be exploited to produce new DSP tools of surprising utility, highly suited to the contemporary world of pervasive digital sensors and high-powered, yet cheap, computing hardware. This book gives a solid mathematical foundation to, and details the key concepts and algorithms in this important topic.

DKK 769.00
1

Project X Origins: Dark Red+ Book band, Oxford Level 19: Fears and Frights: The Fear Machine - J.a. Henderson - Bog - Oxford University Press -

Donald Michie: machine intelligence, biology and more - Ashwin Srinivasan - Bog - Oxford University Press - Plusbog.dk

Human-Like Machine Intelligence - - Bog - Oxford University Press - Plusbog.dk

The Time Machine - H. G. Wells - Bog - Oxford University Press - Plusbog.dk

The Volatility Machine - Michael (adjunct Professor Pettis - Bog - Oxford University Press - Plusbog.dk

The Volatility Machine - Michael (adjunct Professor Pettis - Bog - Oxford University Press - Plusbog.dk

This book presents a radically different argument for what has caused, and likely will continue to cause, the collapse of emerging market economies. Pettis combines the insights of economic history, economic theory, and finance theory into a comprehensive model for understanding sovereign liability management and the causes of financial crises. He examines recent financial crises in emerging market countries along with the history of international lending since the 1820s to argue that the process of international lending is driven primarily by external events and not by local politics and/or economic policies. He draws out the corporate finance implications of this approach to argue that most of the current analyses of the recent financial crises suffered by Latin America, Asia, and Russia have largely missed the point. He then develops a sovereign finance model, analogous to corporate finance, to understand the capital structure needs of emerging market countries. Using this model, he finally puts into perspective the recent crises, a new sovereign liability management theory, the implications of the model for sovereign debt restructurings, and the new financial architecture. Bridging the gap between finance specialists and traders, on the one hand, and economists and policy-makers on the other, The Volatility Machine is critical reading for anyone interested in where the international economy is going over the next several years.

DKK 509.00
1

Project X Origins: Grey Book Band, Oxford Level 13: Great Escapes: The X-Machine - Tony Bradman - Bog - Oxford University Press - Plusbog.dk

Oxford Reading Tree TreeTops Chucklers: Level 12: The Ghost in the Washing Machine - John Foster - Bog - Oxford University Press - Plusbog.dk