The question of memory recovery is now more important than ever with the controversy over delayed recall and false memory having spilled over from psychology to the courts and the public media. The Recovery of Unconscious Memories provides a comprehensive scientific treatment of a century of research that integrates for the first time the findings of the clinic and the laboratory. Included are authoritative treatments of hypnotic hypermnesia, free association and forced recall, the recovery of subliminal stimuli in dreams and fantasy, electrical recall, recovery of sensory-motor skills (also symptoms or "sick skills"), and modern mathematical decision theory analyses of true and false memories. Erdelyi's own ground-breaking research is presented, including his recent discovery of striking memory recoveries in long-delayed recall probes administered months after last testing. In a technical appendix, Erdelyi unveils for the first time a methodological solution to the problem of response bias in narrative recall.
Use this book to learn how you can, at little or no expense, make virtually any movie using Machinima. The authors guide you from making your first Machinima movie to a grounding in both conventional filmmaking and Machinima technology that will let you tackle very complex film projects. The book focuses on the following Machinima platforms: The Sims 2: Arguably the most popular Machinima platform of all time, The Sims 2 allows you to tell stories ranging from romance to noir action. World Of Warcraft: Tell your own tales of heroism in the world of Azeroth, following in the footsteps of award-winning Machinima creators and even the makers of South Park. Medieval 2: Total War - This astonishing new game allows you to create Lord of the Rings-scale medieval battle films using just a home computer! MovieStorm: For the first time, unleash the power of Machinima as a professional user using a fully-featured, fully-licensed commercial Machinima platform. You'll be introduced to all aspects of Machinima production, from live filming in a game through the creation of sets, props and characters, as well as the basics of cinematography, storytelling and sound design.
This book offers a comprehensive introduction to the central ideas that underpin deep learning. It is intended both for newcomers to machine learning and for those already experienced in the field. Covering key concepts relating to contemporary architectures and techniques, this essential book equips readers with a robust foundation for potential future specialization. The field of deep learning is undergoing rapid evolution, and therefore this book focusses on ideas that are likely to endure the test of time. The book is organized into numerous bite-sized chapters, each exploring a distinct topic, and the narrative follows a linear progression, with each chapter building upon content from its predecessors. This structure is well-suited to teaching a two-semester undergraduate or postgraduate machine learning course, while remaining equally relevant to those engaged in active research or in self-study. A full understanding of machine learning requires some mathematical background and so the book includes a self-contained introduction to probability theory. However, the focus of the book is on conveying a clear understanding of ideas, with emphasis on the real-world practical value of techniques rather than on abstract theory. Complex concepts are therefore presented from multiple complementary perspectives including textual descriptions, diagrams, mathematical formulae, and pseudo-code. Chris Bishop is a Technical Fellow at Microsoft and is the Director of Microsoft Research AI4Science. He is a Fellow of Darwin College Cambridge, a Fellow of the Royal Academy of Engineering, and a Fellow of the Royal Society. Hugh Bishop is an Applied Scientist at Wayve, a deep learning autonomous driving company in London, where he designs and trains deep neural networks. He completed his MPhil in Machine Learning and Machine Intelligence at Cambridge University. “Chris Bishop wrote a terrific textbook on neural networks in 1995 and has a deep knowledge of the field and its core ideas. His many years of experience in explaining neural networks have made him extremely skillful at presenting complicated ideas in the simplest possible way and it is a delight to see these skills applied to the revolutionary new developments in the field.” -- Geoffrey Hinton "With the recent explosion of deep learning and AI as a research topic, and the quickly growing importance of AI applications, a modern textbook on the topic was badly needed. The "New Bishop" masterfully fills the gap, covering algorithms for supervised and unsupervised learning, modern deep learning architecture families, as well as how to apply all of this to various application areas." – Yann LeCun “This excellent and very educational book will bring the reader up to date with the main concepts and advances in deep learning with a solid anchoring in probability. These concepts are powering current industrial AI systems and are likely to form the basis of further advances towards artificial general intelligence.” -- Yoshua Bengio
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