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Author: Simant Dube
Publisher: Springer Nature
ISBN: 3030686248
Category : Computers
Languages : en
Pages : 355
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Book Description
This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long adventurous road in the future. An Intuitive Exploration of Artificial Intelligence offers insightful details on how AI works and solves problems in computer vision, natural language understanding, speech understanding, reinforcement learning and synthesis of new content. From the classic problem of recognizing cats and dogs, to building autonomous vehicles, to translating text into another language, to automatically converting speech into text and back to speech, to generating neural art, to playing games, and the author's own experience in building solutions in industry, this book is about explaining how exactly the myriad applications of AI flow out of its immense potential. The book is intended to serve as a textbook for graduate and senior-level undergraduate courses in AI. Moreover, since the book provides a strong geometrical intuition about advanced mathematical foundations of AI, practitioners and researchers will equally benefit from the book.
Author: Simant Dube
Publisher: Springer Nature
ISBN: 3030686248
Category : Computers
Languages : en
Pages : 355
Get Book Here
Book Description
This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long adventurous road in the future. An Intuitive Exploration of Artificial Intelligence offers insightful details on how AI works and solves problems in computer vision, natural language understanding, speech understanding, reinforcement learning and synthesis of new content. From the classic problem of recognizing cats and dogs, to building autonomous vehicles, to translating text into another language, to automatically converting speech into text and back to speech, to generating neural art, to playing games, and the author's own experience in building solutions in industry, this book is about explaining how exactly the myriad applications of AI flow out of its immense potential. The book is intended to serve as a textbook for graduate and senior-level undergraduate courses in AI. Moreover, since the book provides a strong geometrical intuition about advanced mathematical foundations of AI, practitioners and researchers will equally benefit from the book.
Author: Norman Matloff
Publisher: No Starch Press
ISBN: 1718502109
Category : Computers
Languages : en
Pages : 271
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Book Description
Learn to expertly apply a range of machine learning methods to real data with this practical guide. Packed with real datasets and practical examples, The Art of Machine Learning will help you develop an intuitive understanding of how and why ML methods work, without the need for advanced math. As you work through the book, you’ll learn how to implement a range of powerful ML techniques, starting with the k-Nearest Neighbors (k-NN) method and random forests, and moving on to gradient boosting, support vector machines (SVMs), neural networks, and more. With the aid of real datasets, you’ll delve into regression models through the use of a bike-sharing dataset, explore decision trees by leveraging New York City taxi data, and dissect parametric methods with baseball player stats. You’ll also find expert tips for avoiding common problems, like handling “dirty” or unbalanced data, and how to troubleshoot pitfalls. You’ll also explore: How to deal with large datasets and techniques for dimension reduction Details on how the Bias-Variance Trade-off plays out in specific ML methods Models based on linear relationships, including ridge and LASSO regression Real-world image and text classification and how to handle time series data Machine learning is an art that requires careful tuning and tweaking. With The Art of Machine Learning as your guide, you’ll master the underlying principles of ML that will empower you to effectively use these models, rather than simply provide a few stock actions with limited practical use. Requirements: A basic understanding of graphs and charts and familiarity with the R programming language
Author: Nick Bostrom
Publisher:
ISBN: 0199678111
Category : Computers
Languages : en
Pages : 353
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Book Description
This profoundly ambitious and original book picks its way carefully through a vast tract of forbiddingly difficult intellectual terrain.
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309684234
Category : Computers
Languages : en
Pages : 148
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Book Description
Information technology (IT) is widely understood to be the enabling technology of the 21st century. IT has transformed, and continues to transform, all aspects of our lives: commerce and finance, education, energy, health care, manufacturing, government, national security, transportation, communications, entertainment, science, and engineering. IT and its impact on the U.S. economyâ€"both directly (the IT sector itself) and indirectly (other sectors that are powered by advances in IT)â€"continue to grow in size and importance. IT’s impacts on the U.S. economyâ€"both directly (the IT sector itself) and indirectly (other sectors that are powered by advances in IT)â€"continue to grow. IT enabled innovation and advances in IT products and services draw on a deep tradition of research and rely on sustained investment and a uniquely strong partnership in the United States among government, industry, and universities. Past returns on federal investments in IT research have been extraordinary for both U.S. society and the U.S. economy. This IT innovation ecosystem fuels a virtuous cycle of innovation with growing economic impact. Building on previous National Academies work, this report describes key features of the IT research ecosystem that fuel IT innovation and foster widespread and longstanding impact across the U.S. economy. In addition to presenting established computing research areas and industry sectors, it also considers emerging candidates in both categories.
Author: Anirudh Koul
Publisher: "O'Reilly Media, Inc."
ISBN: 1492034819
Category : Computers
Languages : en
Pages : 585
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Book Description
Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users
Author: Donald Tveter
Publisher: Wiley-IEEE Computer Society Press
ISBN:
Category : Computers
Languages : en
Pages : 392
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Book Description
This book pays extra attention to the new ideas in AI: neural networking, case based reasoning, and memory based reasoning, while including the important aspects of traditional symbol processing AI. As much as possible, these methods are compared with each other so that the reader will see the advantages and disadvantages of each method. Second, the new and traditional methods are presented as different ways of doing pattern recognition, giving unity to the subject matter. Third, rather than treating AI as just a collection of advanced algorithms, it also looks at the problems involved in producing the kind of general purpose intelligence found in human beings who have to deal with the real world.
Author: Melanie Mitchell
Publisher: Farrar, Straus and Giroux
ISBN: 0374715238
Category : Computers
Languages : en
Pages : 216
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Book Description
“After reading Mitchell’s guide, you’ll know what you don’t know and what other people don’t know, even though they claim to know it. And that’s invaluable." –The New York Times A leading computer scientist brings human sense to the AI bubble No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.
Author: Prof. Dr. Bilal Semih Bozdemir
Publisher: Prof. Dr. Bilal Semih Bozdemir
ISBN:
Category : Fiction
Languages : en
Pages : 462
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Book Description
Humans and the Third Dimension; A Journey of Discovery The Limits of Our Perceptions Our Three-Dimensional World: A Familiar Reality Space and Time: Basic Concepts The Limits of Human Perception: Sight, Hearing, Touch Other Senses: Smell and Taste The Sixth Sense: Intuition and Insight The Subconscious and the Superconscious: Hidden Worlds Dreams and Reality: Is There a Difference? Parallel Universes: Possibilities and Scenarios Quantum Physics: On the Nature of Reality Quantum Entanglement: Separate But Connected Superposition: Being in More Than One State Quantum Examples: Reflections in Daily Life Time Travel: Is It Possible? The Theory of Relativity of Time: Einstein's Legacy Black Holes: The End of Time? Wormholes: Transitioning from One Dimension to Another The Theory of the Multiverse: Infinite Possibilities The Fourth Dimension and Beyond: Challenges of Conceptualization Human Consciousness and Dimensions: Is There a Connection? Aura and Energy Fields: Invisible Worlds Meditation and Consciousness Expansion: New Perspectives Astral Travel: Unconscious Experiences Telepathy and Remote Influence: Mind Power Dream Interpretation: Signs of the Subconscious Kabbalah and Dimensions: The View of the Ancient Sages Buddhism and Dimensions: Spiritual Development Hinduism and Dimensions: Karma and Reincarnation Shamanism and Dimensions: Spiritual Journeys Human Body and Energy Centers: Chakras Chakra Balancing and Healing: Holistic Approach Frequencies and Vibrations: The Language of Energy Crystals and Energy: Healing and Balance Reiki and Energy Healing: Modern Applications Spiritual Applications: Interdimensional Connections Traces of the Unseen World: Historical Examples Mysterious Events: The Unexplained Phenomenon UFOs and Aliens: Fact or Fiction? Exploration of the Unknown: A Continuous Process Man's Place in the Universe: Existential Questions
Author: Jan J. Koenderink
Publisher: Mit Press
ISBN: 9780262111393
Category : Computers
Languages : en
Pages : 699
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Book Description
Solid Shape gives engineers and applied scientists access to the extensive mathematical literature on three dimensional shapes. Drawing on the author's deep and personal understanding of three-dimensional space, it adopts an intuitive visual approach designed to develop heuristic tools of real use in applied contexts.Increasing activity in such areas as computer aided design and robotics calls for sophisticated methods to characterize solid objects. A wealth of mathematical research exists that can greatly facilitate this work yet engineers have continued to "reinvent the wheel" as they grapple with problems in three dimensional geometry. Solid Shape bridges the gap that now exists between technical and modern geometry and shape theory or computer vision, offering engineers a new way to develop the intuitive feel for behavior of a system under varying situations without learning the mathematicians' formal proofs. Reliance on descriptive geometry rather than analysis and on representations most easily implemented on microcomputers reinforces this emphasis on transforming the theoretical to the practical.Chapters cover shape and space, Euclidean space, curved submanifolds, curves, local patches, global patches, applications in ecological optics, morphogenesis, shape in flux, and flux models. A final chapter on literature research and an appendix on how to draw and use diagrams invite readers to follow their own pursuits in threedimensional shape.Jan J. Koenderinck is Professor in the Department of Physics and Astronomy at Utrecht University. Solid Shape is included in the Artificial Intelligence series, edited by Patrick Winston, Michael Brady, and Daniel Bobrow
Author: Ambreen Hamadani
Publisher: Elsevier
ISBN: 0443240000
Category : Computers
Languages : en
Pages : 370
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Book Description
A Biologist’s Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences provides an overview of the basics of Artificial Intelligence for life science biologists. In 14 chapters/sections, readers will find an introduction to Artificial Intelligence from a biologist’s perspective, including coverage of AI in precision medicine, disease detection, and drug development. The book also gives insights into the AI techniques used in biology and the applications of AI in food, and in environmental, evolutionary, agricultural, and bioinformatic sciences. Final chapters cover ethical issues surrounding AI and the impact of AI on the future. This book covers an interdisciplinary area and is therefore is an important subject matter resource and reference for researchers in biology and students pursuing their degrees in all areas of Life Sciences. It is also a useful title for the industry sector and computer scientists who would gain a better understanding of the needs and requirements of biological sciences and thus better tune the algorithms. Helps biologists succeed in understanding the concepts of Artificial Intelligence and machine learning Equips with new data mining strategies an easy interface into the world of Artificial Intelligence Enables researchers to enhance their own sphere of researching Artificial Intelligence
