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Author: Thomas Lindblad
Publisher: SPIE-International Society for Optical Engineering
ISBN: 9780819432025
Category : Computers
Languages : en
Pages : 622
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Book Description
Author: Thomas Lindblad
Publisher: SPIE-International Society for Optical Engineering
ISBN: 9780819432025
Category : Computers
Languages : en
Pages : 622
Get Book Here
Book Description
Author: Society for Computer Simulation
Publisher: SPIE-International Society for Optical Engineering
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 616
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Book Description
Author: Magnus Ekman
Publisher: Addison-Wesley Professional
ISBN: 0137470290
Category : Computers
Languages : en
Pages : 1106
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Book Description
NVIDIA's Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results "To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards accomplishing these lofty goals." -- From the foreword by Dr. Anima Anandkumar, Bren Professor, Caltech, and Director of ML Research, NVIDIA "Ekman uses a learning technique that in our experience has proven pivotal to success—asking the reader to think about using DL techniques in practice. His straightforward approach is refreshing, and he permits the reader to dream, just a bit, about where DL may yet take us." -- From the foreword by Dr. Craig Clawson, Director, NVIDIA Deep Learning Institute Deep learning (DL) is a key component of today's exciting advances in machine learning and artificial intelligence. Learning Deep Learning is a complete guide to DL. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, this book is ideal for developers, data scientists, analysts, and others--including those with no prior machine learning or statistics experience. After introducing the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, and recurrent layers, Magnus Ekman shows how to use them to build advanced architectures, including the Transformer. He describes how these concepts are used to build modern networks for computer vision and natural language processing (NLP), including Mask R-CNN, GPT, and BERT. And he explains how a natural language translator and a system generating natural language descriptions of images. Throughout, Ekman provides concise, well-annotated code examples using TensorFlow with Keras. Corresponding PyTorch examples are provided online, and the book thereby covers the two dominating Python libraries for DL used in industry and academia. He concludes with an introduction to neural architecture search (NAS), exploring important ethical issues and providing resources for further learning. Explore and master core concepts: perceptrons, gradient-based learning, sigmoid neurons, and back propagation See how DL frameworks make it easier to develop more complicated and useful neural networks Discover how convolutional neural networks (CNNs) revolutionize image classification and analysis Apply recurrent neural networks (RNNs) and long short-term memory (LSTM) to text and other variable-length sequences Master NLP with sequence-to-sequence networks and the Transformer architecture Build applications for natural language translation and image captioning NVIDIA's invention of the GPU sparked the PC gaming market. The company's pioneering work in accelerated computing--a supercharged form of computing at the intersection of computer graphics, high-performance computing, and AI--is reshaping trillion-dollar industries, such as transportation, healthcare, and manufacturing, and fueling the growth of many others. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Author: Jeb Blount
Publisher: John Wiley & Sons
ISBN: 1119755832
Category : Business & Economics
Languages : en
Pages : 279
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Book Description
Remote learning has been around since the 18th century. Caleb Phillips began advertising correspondence courses in the Boston Gazette in 1728 allowing people, for the first time, to learn new skills no matter where they lived. For the past 300 years, virtual training, in its various formats, has been meandering into shore on an inevitable yet slow building tide. And then, just like that, everything changed. A global pandemic. Social distancing. Working from home. In an instant, the tide became a tsunami. The global pandemic accelerated the broad adoption of virtual instructor led training along with awareness that classroom-based training is often expensive, inefficient, and fails to deliver a fair return on investment. While it is certainly more challenging to re-create the collaborative environment of the physical classroom in a virtual setting, virtual training combines the structure, accountability, and social learning benefits of classroom training with speed, agility, and significant cost savings. Simply put, virtual training enables organizations to rapidly upskill more people, while generating a far higher return on the training investment. Virtual training is also green. Studies indicate that virtual training consumes nearly 90% less energy and produces 85% fewer CO2 emissions than classroom training. Still, the biggest challenge with virtual training, and the reason there has been so much resistance to it, is historically the experience has been excruciating. Not the quality of the curriculum or content. Not the talent of the trainer. The learning experience. There are few people who haven’t had the pleasure of sitting through agonizing virtual training sessions. Death by voice over PowerPoint, delivered by a disengaged instructor, has an especially bitter flavor. It is the way virtual training is delivered that matters most. When the virtual learning experience is emotionally positive: Participants are more engaged, embrace new competencies, and knowledge sticks Participants are more likely to show up to class and be open to future virtual training Trainers enjoy their work and gain fulfillment from making an impact Leaders book more virtual training Organizations more readily blend and integrate virtual training into learning & development initiatives This is exactly what this book is about. Virtual Training is the definitive guide to delivering virtual training that engages learners and makes new skills and behavioral changes stick. Jeb Blount, one of the most celebrated trainers and authors of our generation, walks you step-by-step through the seven elements of effective, engaging virtual learning experiences. Trainer Mindset & Emotional Discipline Production & Technology Media & Visuals Virtual Curriculum & Instructional Design Planning & Preparation Virtual Communication Skills Dynamic & Interactive Training Delivery As you dive into these powerful insights, and with each new chapter, you’ll gain greater and greater confidence in your ability to effectively deliver training in a virtual classroom. Once you master virtual training delivery and experience the power of remote learning, you may never want to go back to the physical classroom again.
Author: Yao Ma
Publisher: Cambridge University Press
ISBN: 1108831745
Category : Computers
Languages : en
Pages : 339
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Book Description
A comprehensive text on foundations and techniques of graph neural networks with applications in NLP, data mining, vision and healthcare.
Author: Georgios N. Yannakakis
Publisher: Springer
ISBN: 3319635190
Category : Computers
Languages : en
Pages : 350
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Book Description
This is the first textbook dedicated to explaining how artificial intelligence (AI) techniques can be used in and for games. After introductory chapters that explain the background and key techniques in AI and games, the authors explain how to use AI to play games, to generate content for games and to model players. The book will be suitable for undergraduate and graduate courses in games, artificial intelligence, design, human-computer interaction, and computational intelligence, and also for self-study by industrial game developers and practitioners. The authors have developed a website (http://www.gameaibook.org) that complements the material covered in the book with up-to-date exercises, lecture slides and reading.
Author: Marco Iansiti
Publisher: Harvard Business Press
ISBN: 1633697630
Category : Business & Economics
Languages : en
Pages : 181
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Book Description
"a provocative new book" — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.
Author: Leonard Barolli
Publisher: Springer
ISBN: 3030150356
Category : Technology & Engineering
Languages : en
Pages : 1217
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Book Description
The aim of the book is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of Web Computing, Intelligent Systems and Internet Computing. As the Web has become a major source of information, techniques and methodologies that extract quality information are of paramount importance for many Web and Internet applications. Data mining and knowledge discovery play key roles in many of today’s prominent Web applications such as e-commerce and computer security. Moreover, the outcome of Web services delivers a new platform for enabling service-oriented systems. The emergence of large scale distributed computing paradigms, such as Cloud Computing and Mobile Computing Systems, has opened many opportunities for collaboration services, which are at the core of any Information System. Artificial Intelligence (AI) is an area of computer science that build intelligent systems and algorithms that work and react like humans. The AI techniques and computational intelligence are powerful tools for learning, adaptation, reasoning and planning. They have the potential to become enabling technologies for the future intelligent networks. Recent research in the field of intelligent systems, robotics, neuroscience, artificial intelligence and cognitive sciences are very important for the future development and innovation of Web and Internet applications.
Author: Qiang Yang
Publisher: Springer Nature
ISBN: 3030630765
Category : Computers
Languages : en
Pages : 291
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Book Description
This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated learning model against different types of attacks such as data leakage and/or data poisoning. Secondly, the book presents incentive mechanisms which aim to encourage individuals to participate in the federated learning ecosystems. Last but not least, this book also describes how federated learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both the academia and the industry, who would like to learn about federated learning, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing would be helpful.”
Author: Juan A. Botía
Publisher: IOS Press
ISBN: 1614990794
Category : Computers
Languages : en
Pages : 468
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Book Description
This book presents the proceedings of the workshops of the 8th International Conference on IntelligentEnvironments IE 12, held in Guanajuato, Mexico, in June 2012. Topics covered in the workshops includeintelligent environments supporting healthcare and well-being artificial intelligence techniques for ambientintelligence large-scale intelligent environments intelligent domestic robots intelligent environmenttechnology in education multimodal interfaces applied in skills transfer, healthcare and rehabilitation thereliability of intelligent environments and improving industrial automation using
