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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.
Dive into the groundbreaking world of artificial intelligence with Adaptive Computation and Machine Learning: Deep Learning (Hardcover). This meticulously curated book provides an in-depth understanding of deep learning concepts, paving the way for both aspiring and seasoned data scientists to harness the potential of advanced neural networks and computational models. Whether you’re an academic researcher or a professional developer, this guide is packed with invaluable insights to help you stay ahead in the rapidly evolving field of machine learning.
Presented in a durable hardcover format, this book is built for longevity, making it an ideal addition to your personal library or workplace reference shelf. Its structured chapters offer clear explanations, while maintaining a logical flow to accommodate readers of varying expertise levels. The physical edition ensures you get the stability and convenience of a book crafted to endure prolonged use. Additionally, the hardcover binding adds a touch of elegance, making it a thoughtful gift for fellow AI enthusiasts or professionals looking to expand their technical repertoire.
Adaptive Computation and Machine Learning: Deep Learning covers all essential aspects of the field, from foundational principles to cutting-edge advancements. Featuring discussions about deep neural networks, optimization algorithms, and innovative applications, the book offers readers an opportunity to understand both the theory and practical implementation of deep learning systems. Through illustrative examples, case studies, and step-by-step guides, this hardcover edition caters to a wide range of learning objectives—from understanding basic architectures to solving complex computational problems.
This book bridges the gap between academic rigor and real-world applicability, making it an indispensable resource in key areas such as artificial intelligence research, natural language processing, computer vision, and decision-making systems. With contributions from leading experts in the domain, you’re set to gain valuable insights directly from pioneers who are shaping the future of deep learning technologies.
Whether you’re a student, researcher, or professional, Adaptive Computation and Machine Learning: Deep Learning (Hardcover) is tailored to meet your learning needs. Find clarity on complex topics, improve your problem-solving skills, and explore the latest innovations in computation-driven intelligence. Enrich your knowledge and fuel your curiosity with this essential guide that serves as both a practical handbook and a source of inspiration for delving deeper into the dynamic world of AI.
Transform your understanding of machine learning and deep learning systems with this remarkable hardcover reference. Add it to your collection today and take a confident leap into the future of adaptive computation!
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