Author: Alexander Philip
Publisher:
ISBN:
Category : Knowledge, Theory of
Languages : en
Pages : 340
Book Description
The Dynamic Foundation of Knowledge
Author: Alexander Philip
Publisher:
ISBN:
Category : Knowledge, Theory of
Languages : en
Pages : 340
Book Description
Publisher:
ISBN:
Category : Knowledge, Theory of
Languages : en
Pages : 340
Book Description
Foundations of Machine Learning, second edition
Author: Mehryar Mohri
Publisher: MIT Press
ISBN: 0262351366
Category : Computers
Languages : en
Pages : 505
Book Description
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and VC-dimension; Support Vector Machines (SVMs); kernel methods; boosting; on-line learning; multi-class classification; ranking; regression; algorithmic stability; dimensionality reduction; learning automata and languages; and reinforcement learning. Each chapter ends with a set of exercises. Appendixes provide additional material including concise probability review. This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition.
Publisher: MIT Press
ISBN: 0262351366
Category : Computers
Languages : en
Pages : 505
Book Description
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and VC-dimension; Support Vector Machines (SVMs); kernel methods; boosting; on-line learning; multi-class classification; ranking; regression; algorithmic stability; dimensionality reduction; learning automata and languages; and reinforcement learning. Each chapter ends with a set of exercises. Appendixes provide additional material including concise probability review. This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition.
The Knowledge Machine: How Irrationality Created Modern Science
Author: Michael Strevens
Publisher: Liveright Publishing
ISBN: 1631491385
Category : Science
Languages : en
Pages : 368
Book Description
“The Knowledge Machine is the most stunningly illuminating book of the last several decades regarding the all-important scientific enterprise.” —Rebecca Newberger Goldstein, author of Plato at the Googleplex A paradigm-shifting work, The Knowledge Machine revolutionizes our understanding of the origins and structure of science. • Why is science so powerful? • Why did it take so long—two thousand years after the invention of philosophy and mathematics—for the human race to start using science to learn the secrets of the universe? In a groundbreaking work that blends science, philosophy, and history, leading philosopher of science Michael Strevens answers these challenging questions, showing how science came about only once thinkers stumbled upon the astonishing idea that scientific breakthroughs could be accomplished by breaking the rules of logical argument. Like such classic works as Karl Popper’s The Logic of Scientific Discovery and Thomas Kuhn’s The Structure of Scientific Revolutions, The Knowledge Machine grapples with the meaning and origins of science, using a plethora of vivid historical examples to demonstrate that scientists willfully ignore religion, theoretical beauty, and even philosophy to embrace a constricted code of argument whose very narrowness channels unprecedented energy into empirical observation and experimentation. Strevens calls this scientific code the iron rule of explanation, and reveals the way in which the rule, precisely because it is unreasonably close-minded, overcomes individual prejudices to lead humanity inexorably toward the secrets of nature. “With a mixture of philosophical and historical argument, and written in an engrossing style” (Alan Ryan), The Knowledge Machine provides captivating portraits of some of the greatest luminaries in science’s history, including Isaac Newton, the chief architect of modern science and its foundational theories of motion and gravitation; William Whewell, perhaps the greatest philosopher-scientist of the early nineteenth century; and Murray Gell-Mann, discoverer of the quark. Today, Strevens argues, in the face of threats from a changing climate and global pandemics, the idiosyncratic but highly effective scientific knowledge machine must be protected from politicians, commercial interests, and even scientists themselves who seek to open it up, to make it less narrow and more rational—and thus to undermine its devotedly empirical search for truth. Rich with illuminating and often delightfully quirky illustrations, The Knowledge Machine, written in a winningly accessible style that belies the import of its revisionist and groundbreaking concepts, radically reframes much of what we thought we knew about the origins of the modern world.
Publisher: Liveright Publishing
ISBN: 1631491385
Category : Science
Languages : en
Pages : 368
Book Description
“The Knowledge Machine is the most stunningly illuminating book of the last several decades regarding the all-important scientific enterprise.” —Rebecca Newberger Goldstein, author of Plato at the Googleplex A paradigm-shifting work, The Knowledge Machine revolutionizes our understanding of the origins and structure of science. • Why is science so powerful? • Why did it take so long—two thousand years after the invention of philosophy and mathematics—for the human race to start using science to learn the secrets of the universe? In a groundbreaking work that blends science, philosophy, and history, leading philosopher of science Michael Strevens answers these challenging questions, showing how science came about only once thinkers stumbled upon the astonishing idea that scientific breakthroughs could be accomplished by breaking the rules of logical argument. Like such classic works as Karl Popper’s The Logic of Scientific Discovery and Thomas Kuhn’s The Structure of Scientific Revolutions, The Knowledge Machine grapples with the meaning and origins of science, using a plethora of vivid historical examples to demonstrate that scientists willfully ignore religion, theoretical beauty, and even philosophy to embrace a constricted code of argument whose very narrowness channels unprecedented energy into empirical observation and experimentation. Strevens calls this scientific code the iron rule of explanation, and reveals the way in which the rule, precisely because it is unreasonably close-minded, overcomes individual prejudices to lead humanity inexorably toward the secrets of nature. “With a mixture of philosophical and historical argument, and written in an engrossing style” (Alan Ryan), The Knowledge Machine provides captivating portraits of some of the greatest luminaries in science’s history, including Isaac Newton, the chief architect of modern science and its foundational theories of motion and gravitation; William Whewell, perhaps the greatest philosopher-scientist of the early nineteenth century; and Murray Gell-Mann, discoverer of the quark. Today, Strevens argues, in the face of threats from a changing climate and global pandemics, the idiosyncratic but highly effective scientific knowledge machine must be protected from politicians, commercial interests, and even scientists themselves who seek to open it up, to make it less narrow and more rational—and thus to undermine its devotedly empirical search for truth. Rich with illuminating and often delightfully quirky illustrations, The Knowledge Machine, written in a winningly accessible style that belies the import of its revisionist and groundbreaking concepts, radically reframes much of what we thought we knew about the origins of the modern world.
Foundations of Knowledge
Author: E. P. Papanoutsos
Publisher: SUNY Press
ISBN: 9780873950343
Category : Philosophy
Languages : en
Pages : 360
Book Description
"The inquiry into the foundations of knowledge is a systematic inquiry into the problem of truth. This problem constitutes one of the three main concerns of philosophical analysis, the others being the problem of beauty and the problem of goodness." Thus Evangelos P. Papanoutsos, Greece's leading contemporary philosopher, introduces this third book of his "Trilogy of the Mind." The first two volumes covered aesthetics and ethics; this one is a major work in epistemology. Combining rigorous analysis with thorough-going scholarship, displaying an intimate acquaintance with the physical and humanistic sciences, and drawing on a deep understanding of philosophical method and the history of philosophy, Professor Papanoutsos is held in high esteem by his European colleagues. This translation of his masterpiece will enhance his reputation and influence among readers of English. The themes of The Foundation of Knowledge range over the topics that have been continually challenging to the modern era of philosophers: being and consciousness, experience and reason, common sense and science, and the domains of knowledge, including the nature of philosophical knowledge. Special attention is paid to the analysis of theoretical consciousness, the problems of categorical thinking, the theory of judgment, mathematics and logic, and the limits of historical understanding.
Publisher: SUNY Press
ISBN: 9780873950343
Category : Philosophy
Languages : en
Pages : 360
Book Description
"The inquiry into the foundations of knowledge is a systematic inquiry into the problem of truth. This problem constitutes one of the three main concerns of philosophical analysis, the others being the problem of beauty and the problem of goodness." Thus Evangelos P. Papanoutsos, Greece's leading contemporary philosopher, introduces this third book of his "Trilogy of the Mind." The first two volumes covered aesthetics and ethics; this one is a major work in epistemology. Combining rigorous analysis with thorough-going scholarship, displaying an intimate acquaintance with the physical and humanistic sciences, and drawing on a deep understanding of philosophical method and the history of philosophy, Professor Papanoutsos is held in high esteem by his European colleagues. This translation of his masterpiece will enhance his reputation and influence among readers of English. The themes of The Foundation of Knowledge range over the topics that have been continually challenging to the modern era of philosophers: being and consciousness, experience and reason, common sense and science, and the domains of knowledge, including the nature of philosophical knowledge. Special attention is paid to the analysis of theoretical consciousness, the problems of categorical thinking, the theory of judgment, mathematics and logic, and the limits of historical understanding.
Machine Learning Foundations
Author: Taeho Jo
Publisher: Springer Nature
ISBN: 3030659003
Category : Technology & Engineering
Languages : en
Pages : 391
Book Description
This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning techniques. The book consists of four parts: foundation, supervised learning, unsupervised learning, and advanced learning. The first part provides the fundamental materials, background, and simple machine learning algorithms, as the preparation for studying machine learning algorithms. The second and the third parts provide understanding of the supervised learning algorithms and the unsupervised learning algorithms as the core parts. The last part provides advanced machine learning algorithms: ensemble learning, semi-supervised learning, temporal learning, and reinforced learning. Provides comprehensive coverage of both learning algorithms: supervised and unsupervised learning; Outlines the computation paradigm for solving classification, regression, and clustering; Features essential techniques for building the a new generation of machine learning.
Publisher: Springer Nature
ISBN: 3030659003
Category : Technology & Engineering
Languages : en
Pages : 391
Book Description
This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning techniques. The book consists of four parts: foundation, supervised learning, unsupervised learning, and advanced learning. The first part provides the fundamental materials, background, and simple machine learning algorithms, as the preparation for studying machine learning algorithms. The second and the third parts provide understanding of the supervised learning algorithms and the unsupervised learning algorithms as the core parts. The last part provides advanced machine learning algorithms: ensemble learning, semi-supervised learning, temporal learning, and reinforced learning. Provides comprehensive coverage of both learning algorithms: supervised and unsupervised learning; Outlines the computation paradigm for solving classification, regression, and clustering; Features essential techniques for building the a new generation of machine learning.
Mind
Author:
Publisher:
ISBN:
Category : Philosophy
Languages : en
Pages : 630
Book Description
A journal of philosophy covering epistemology, metaphysics, philosophy of language, philosophy of logic, and philosophy of mind.
Publisher:
ISBN:
Category : Philosophy
Languages : en
Pages : 630
Book Description
A journal of philosophy covering epistemology, metaphysics, philosophy of language, philosophy of logic, and philosophy of mind.
The Nation
Author:
Publisher:
ISBN:
Category : Current events
Languages : en
Pages : 646
Book Description
Publisher:
ISBN:
Category : Current events
Languages : en
Pages : 646
Book Description
Bookseller and the Stationery Trades' Journal
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 2022
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 2022
Book Description
Books of 1911-
Author: Chicago Public Library
Publisher:
ISBN:
Category : Best books
Languages : en
Pages : 170
Book Description
Publisher:
ISBN:
Category : Best books
Languages : en
Pages : 170
Book Description
Sale
Author: Anderson Galleries, Inc
Publisher:
ISBN:
Category : Art
Languages : en
Pages : 828
Book Description
Publisher:
ISBN:
Category : Art
Languages : en
Pages : 828
Book Description