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From Pixels to Insights

Exploring Machine and Deep Learning's Impact on Computer Vision

Learn to secure, build, implement, and test future blockchain applications Blockchain was originally introduced in the crypto-currency of Bitcoin in order to keep track of transactions over a peer-to-peer network to prevent the double-spending of bitcoin. This distributed ledger technology, however, has developed a reputation as a disruptive technology for the transfer of values and disintermediation. Despite this reputation, blockchain is, simply, at its core, a data structure-in this case, a cryptographic hash chain of blocks of transactions-continually replicated and maintained in a distributed manner by a peer-to-peer network of hosts. Together they decide through a specific consensus protocol, what transactions can be registered or added to the blockchain. Blockchain Application Security introduces the reader to the architecture and components of blockchain, as well as blockchain and bitcoin protocol, aimed at a basic level of understanding of the technical perspective. The book discusses the benefits, the vulnerabilities, and even the design flaws found in blockchain applications. It also teaches how to manage the risks of blockchain by deciding how digital assets, data confidentiality, and data availability should be protected from unauthorized access. Blockchain Application Security readers will also find: <ul> <li>An exploration of source code and core APIs relevant to blockchain</li> <li>A glossary of common terminology used for blockchain</li> <li>Real cases of blockchain applications to illustrate points</li></ul>Blockchain Application Security is an ideal resource for application architects, software developers, security auditors, and vulnerability testers of enterprise-based blockchain applications.

How to Design Secure and Attack Resilient Blockchain Applications

Blockchain Application Security

IEEE Press Series on Offshore Wind Energy

Weak Grid Integration of Inverter-Based Resources

Why Change Is Hard and How We Can Achieve It

New Beginnings

Triangulating AI Security

Machine Learning in Biomedical Science and Healthcare Informatics

Medical Analytics for Clinical and Healthcare Applications

Vital information on AI, ML, and 5G, and implementing these topics for cellular network design and optimization AI for Design and Optimization of Cellular Networks focuses on the intersection of cellular communications and AI, discussing current advances, key concepts, challenges, opportunities, and lifecycle management. Divided into two parts, the first part provides the background of AI and cellular communications, exploring the challenges that are associated with creation, deployment, operation, and maintenance of systems for the design and optimization of cellular networks. The second part explains the process of network planning, design, and optimization of cellular networks, including examples and use cases in each area. The second part also discusses the application of AI to energy saving, the challenges that operators face, and a glimpse of future trends for AI, cellular networks, and their related NDO (Network Design and Optimization) activities. The book also includes coverage of AI-powered design technologies, performance characterization of advanced antenna systems, propagation predictions, and more. With heavy contribution from industry professionals at Ericsson, AI for Design and Optimization of Cellular Networks includes detailed information on: Evolution of cellular communications from the early GSM days until today, with special emphasis on the arrival of 5G and its implications compared with LTESupervised, unsupervised, semi-supervised, and reinforcement learning with an intuitive focus, covering their distinctive characteristicsDifferent types of digital twins, their fundamental properties, their suitability for design and optimization of cellular networks, and using them together with AI techniquesTransition from traditional network performance management and operations towards an AI-driven combination of control loops An informed and timely exploration of key developments and challenges by those who work on the frontline, AI for Design and Optimization of Cellular Networks is an essential resource for professionals working in cellular communications and AI, providing a one-of-a-kind blend of practical and theoretical information.

AI for Design and Optimization of Cellular Networks

Shortest Histories

The Shortest History of AI

How AI Learned to Talk and What It Means

These Strange New Minds

The Blueprint for AI Adoption and Societal Transformation

Frameworks and Scorecards for Human-AI Alignment

Move First, Align Fast

A complete guide to deep neural networks – the technology behind AI – covering fundamental and advanced techniques to apply machine learning in real-world scenarios. Deep Learning Crash Course goes beyond the basics of machine learning to delve into modern techniques and applications of great interest right now, and whose popularity will only grow in the future. The book covers topics such as generative models (the technology behind deep fakes), self-supervised learning, attention mechanisms (the tech behind ChatGPT), graph neural networks (the tech behind AlphaFold), and deep reinforcement learning (the tech behind AlphaGo). This book bridges the gap between theory and practice, helping readers gain the confidence to apply deep learning in their work.

Deep Learning Crash Course

Challenges and Applications of Generative Large Language Models

From Pixels to Insights

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