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Author:
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 816
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Book Description
Author:
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 816
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Book Description
Author: Chi Wang
Publisher: Simon and Schuster
ISBN: 1638352151
Category : Computers
Languages : en
Pages : 358
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Book Description
A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the deep learning development cycle Automate training for models in TensorFlow and PyTorch Optimize dataset management, training, model serving and hyperparameter tuning Pick the right open-source project for your platform Deep learning systems are the components and infrastructure essential to supporting a deep learning model in a production environment. Written especially for software engineers with minimal knowledge of deep learning’s design requirements, Designing Deep Learning Systems is full of hands-on examples that will help you transfer your software development skills to creating these deep learning platforms. You’ll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting—and lucrative—career as a deep learning engineer. About the technology To be practically usable, a deep learning model must be built into a software platform. As a software engineer, you need a deep understanding of deep learning to create such a system. Th is book gives you that depth. About the book Designing Deep Learning Systems: A software engineer's guide teaches you everything you need to design and implement a production-ready deep learning platform. First, it presents the big picture of a deep learning system from the developer’s perspective, including its major components and how they are connected. Then, it carefully guides you through the engineering methods you’ll need to build your own maintainable, efficient, and scalable deep learning platforms. What's inside The deep learning development cycle Automate training in TensorFlow and PyTorch Dataset management, model serving, and hyperparameter tuning A hands-on deep learning lab About the reader For software developers and engineering-minded data scientists. Examples in Java and Python. About the author Chi Wang is a principal software developer in the Salesforce Einstein group. Donald Szeto was the co-founder and CTO of PredictionIO. Table of Contents 1 An introduction to deep learning systems 2 Dataset management service 3 Model training service 4 Distributed training 5 Hyperparameter optimization service 6 Model serving design 7 Model serving in practice 8 Metadata and artifact store 9 Workflow orchestration 10 Path to production
Author: Stephen Carpenteri
Publisher: Skyhorse Publishing Inc.
ISBN: 1616088435
Category : Antiques & Collectibles
Languages : en
Pages : 609
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Book Description
Provides descriptions, prices, and photographs of small firearms.
Author: University of Illinois (Urbana-Champaign campus)
Publisher:
ISBN:
Category :
Languages : en
Pages : 554
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Book Description
Author: Douglas D. Mooney
Publisher: American Mathematical Society
ISBN: 1470466163
Category : Mathematics
Languages : en
Pages : 431
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Book Description
The emphasis of this book lies in the teaching of mathematical modeling rather than simply presenting models. To this end the book starts with the simple discrete exponential growth model as a building block, and successively refines it. This involves adding variable growth rates, multiple variables, fitting growth rates to data, including random elements, testing exactness of fit, using computer simulations and moving to a continuous setting. No advanced knowledge is assumed of the reader, making this book suitable for elementary modeling courses. The book can also be used to supplement courses in linear algebra, differential equations, probability theory and statistics.
Author: Ziheng Sun
Publisher: Elsevier
ISBN: 0323972160
Category : Science
Languages : en
Pages : 430
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Book Description
Artificial Intelligence in Earth Science: Best Practices and Fundamental Challenges provides a comprehensive, step-by-step guide to AI workflows for solving problems in Earth Science. The book focuses on the most challenging problems in applying AI in Earth system sciences, such as training data preparation, model selection, hyperparameter tuning, model structure optimization, spatiotemporal generalization, transforming model results into products, and explaining trained models. In addition, it provides full-stack workflow tutorials to help walk readers through the whole process, regardless of previous AI experience. The book tackles the complexity of Earth system problems in AI engineering, fully guiding geoscientists who are planning to implement AI in their daily work. - Provides practical, step-by-step guides for Earth Scientists who are interested in implementing AI techniques in their work - Features case studies to show real-world examples of techniques described in the book - Includes additional elements to help readers who are new to AI, including end-of-chapter, key concept bulleted lists that concisely cover key concepts in the chapter
Author: Daniel J. Moran
Publisher: Academic Press
ISBN: 0125060416
Category : Education
Languages : en
Pages : 408
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Book Description
"A compendium of empirically verified instructional methods derived from research in behavioral analysis. Coverage includes precision teaching, direct instruction, computerized teaching, and personalized system of instruction, as well as discussing the use of peer tutoring, and chapters specific to teaching language, cognition, grammar and writing"--Book jacket.
Author: Bompa, Tudor
Publisher: Human Kinetics
ISBN: 1450469434
Category : Sports & Recreation
Languages : en
Pages : 368
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Book Description
Periodization authority Tudor Bompa and strength and conditioning expert Carlo Buzzichelli eliminate the guesswork and establish a clear path to reaching peak physical condition and gaining a competitive edge. Periodization Training for Sports includes programs and training models for 35 sports.
Author: Fausto Pedro García Márquez
Publisher: Springer Nature
ISBN: 3031537173
Category :
Languages : en
Pages : 540
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Book Description
Author: Matthias Wingens
Publisher: Springer Nature
ISBN: 3658374667
Category : Social Science
Languages : en
Pages : 250
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Book Description
This introductory book provides an insight into sociological life course research and informs about its theoretical assumptions, analytical concepts and main results. Sociological life course research - like biographical research - has developed into an independent and fruitful field of research since the end of the 1960s. It is true that half a century earlier, in their famous study of "The Polish Peasant in Europe and America" (1918-20), Thomas and Znaniecki had already used life records to examine the connection between social change, social structures, and the life histories of individuals. However, such a research perspective was supplanted by other methodological-conceptual approaches to empirical social research for over fifty years. It was not until the 1960s that sociological interest in life course and biographical theoretical issues reawakened. Today, life course research is considered one of the most important conceptual innovations in sociology in recent decades. The content The life course as a social construction - What is "life course research"? - The life course as an institution - Collective life courses: generations, cohorts and social change - Structures of the life course - Life course research - a conceptual perspective - Life course research, quo vadis? The author Prof. Dr. Matthias Wingens teaches sociology at the University of Bremen, Bremen International Graduate School of Social Sciences (BIGSSS).
