Deep Learning (Adaptive Computation and Machine Learning series) (1版)

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An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Introduction to Artificial Intelligence and Machine Learning (1版)

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【簡介】 Helps students unlock the power of AI and Machine Learning to achieve business success and future-proof their careersArtificial intelligence and machine learning are transforming the modern workplace, making AI literacy a critical skill for business professionals. Introduction to Artificial Intelligence and Machine Learning equips students with essential AI/ML knowledge and practical skills, enabling them to leverage cutting-edge technology in today’s data-driven world. With an engaging and accessible approach, this textbook ensures that students--regardless of technical background--gain a working knowledge of AI/ML systems. Concise, easy-to-digest chapters blend foundational concepts with real-world applications to help students develop the expertise needed to implement AI/ML solutions across industries. For instructors, the textbook offers flexible teaching methodologies, whether focusing on conceptual discussions, light technology applications, or full AI/ML projects. With a clear business perspective and a strong emphasis on AI governance and deployment, the textbook prepares students to navigate the future of AI in the workplace with confidence. Helping students build a solid foundation in key concepts while exploring strategic implementation and ethical considerations, Introduction to Artificial Intelligence and Machine Learning is ideal for undergraduate and graduate students in business, engineering, and healthcare programs taking courses such as Business Analytics, Information Systems, and AI Strategy. AN INTERACTIVE, MULTIMEDIA LEARNING EXPERIENCEThis textbook includes access to an interactive, multimedia e-text. Icons throughout the print book signal corresponding digital content in the e-text. Video Clips created by the author complement the text and engage students more deeply with AI/ML concepts and applications.Interactive Figures and Charts are integrated throughout the enhanced e-text to provide engaging visual representations of the material.Interactive Questions appear in each chapter of the enhanced e-text, providing students with immediate feedback to strengthen learning.