skansi sandro (15 Ergebnisse)

Paperback. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Zustand: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

1st ed. 2020. VIII, 140 p. Softcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

Zustand: New.

Zustand: New. In.

Paperback. Zustand: Brand New. 191 pages. 9.25x6.00x0.75 inches. In Stock.

Zustand: Very good.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive style, explaining the mathematical derivations in a step-by-step manner. The content coverage includes convolutional networks, LSTMs, Word2vec, RBMs, DBNs, neural Turing machines, memory networks and autoencoders. Numerous examples in working Python code are provided throughout the book, and the code is also supplied separately at an accompanying website.Topics and features: introduces the fundamentals of machine learning, and the mathematical and computational prerequisites for deep learning; discusses feed-forward neural networks, and explores the modifications to these which can be applied to any neural network; examines convolutional neural networks, and the recurrent connections to a feed-forward neural network; describes the notion of distributed representations, the concept of the autoencoder, and the ideas behind language processing with deep learning; presents a brief history of artificial intelligence and neural networks, and reviews interesting open research problems in deep learning and connectionism.This clearly written and lively primer on deep learning is essential reading for graduate and advanced undergraduate students of computer science, cognitive science and mathematics, as well as fields such as linguistics, logic, philosophy, and psychology.

Zustand: New. In.

Taschenbuch. Zustand: Neu. Introduction to Deep Learning | From Logical Calculus to Artificial Intelligence | Sandro Skansi | Taschenbuch | Undergraduate Topics in Computer Science | xiii | Englisch | 2018 | Springer | EAN 9783319730035 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Paperback. Zustand: Brand New. 148 pages. 9.25x6.10x0.32 inches. In Stock.

Taschenbuch. Zustand: Neu. Guide to Deep Learning Basics | Logical, Historical and Philosophical Perspectives | Sandro Skansi | Taschenbuch | viii | Englisch | 2021 | Springer | EAN 9783030375935 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the fascinating history of this exciting field, including the pioneering work of Rudolf Carnap, Warren McCulloch, Walter Pitts, Bulcsú László, and Geoffrey Hinton.Topics and features:Provides a brief history of mathematical logic, and discusses the critical role of philosophy, psychology, and neuroscience in the history of AIPresents a philosophical case for the use of fuzzy logic approaches in AIInvestigates the similarities and differences between the Word2vec word embedding algorithm, and the ideas of Wittgenstein and Firth on linguisticsExamines how developments in machine learning provide insights into the philosophical challenge of justifying inductive inferencesDebates, with reference to philosophical anthropology, whether an advanced general artificial intelligence might be considered as a living beingInvestigates the issue of computational complexity through deep-learning strategies for understanding AI-complete problems and developing strong AIExplores philosophical questions at the intersection of AI and transhumanismThis inspirational volume will rekindle a passion for deep learning in those already experienced in coding and studying this discipline, and provide a philosophical big-picture perspective for those new to the field.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the fascinating history of this exciting field, including the pioneering work of Rudolf Carnap, Warren McCulloch, Walter Pitts, Bulcsú László, and Geoffrey Hinton.Topics and features:Provides a brief history of mathematical logic, and discusses the critical role of philosophy, psychology, and neuroscience in the history of AIPresents a philosophical case for the use of fuzzy logic approaches in AIInvestigates the similarities and differences between the Word2vec word embedding algorithm, and the ideas of Wittgenstein and Firth on linguisticsExamines how developments in machine learning provide insights into the philosophical challenge of justifying inductive inferencesDebates, with reference to philosophical anthropology, whether an advanced general artificial intelligence might be considered as a living beingInvestigates the issue of computational complexity through deep-learning strategies for understanding AI-complete problems and developing strong AIExplores philosophical questions at the intersection of AI and transhumanismThis inspirational volume will rekindle a passion for deep learning in those already experienced in coding and studying this discipline, and provide a philosophical big-picture perspective for those new to the field.

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the fascinating history of this exciting field, including the pioneering work of Rudolf Carnap, Warren McCulloch, Walter Pitts, Bulcsú László, and Geoffrey Hinton. Topics and features: Provides a brief history of mathematical logic, and discusses the critical role of philosophy, psychology, and neuroscience in the history of AI Presents a philosophical case for the use of fuzzy logic approaches in AI Investigates the similarities and differences between the Word2vec word embedding algorithm, and the ideas of Wittgenstein and Firth on linguistics Examines how developments in machine learning provide insights into the philosophical challenge of justifying inductive inferences Debates, with reference to philosophical anthropology, whether an advanced general artificial intelligence might be considered as a living being Investigates the issue of computational complexity through deep-learning strategies for understanding AI-complete problems and developing strong AI Explores philosophical questions at the intersection of AI and transhumanism This inspirational volume will rekindle a passion for deep learning in those already experienced in coding and studying this discipline, and provide a philosophical big-picture perspective for those new to the field.