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This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selecta

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Computer Science (R0)

Federico Cecconi

AI in the Financial Markets

New Algorithms and Solutions

&lt;p&gt;Chapter 1. Artificial Intelligence and Financial Markets.- Chapter 2. AI, the overall picture.- Chapter 3. Financial markets: values, dynamics, problems.- Chapter 4. The AI's Role in the Great Reset.- Chapter 5. AI Fintech: find out the truth.- Chapter 6. ABM applications to Financial Markets.- Chapter 7. ML application to the Financial Market.- Chapter 8. AI tools for pricing of distressed asset utp and npl loan portfolios.- Chapter 9. More than data science: FuturICT 2.0.- Chapter 10. Opinion dynamics.&lt;/p&gt;&lt;br&gt;&lt;p&gt;&lt;/p&gt;

Backed by more than 15 years of trading experience, a decade of building automated systems, and five years of managing crypto portfolios, this book is your essential guide to mastering the fast-paced world of digital assets.
Whether you're just starting out or looking to sharpen your edge, you'll find everything you need to succeed—from understanding market cycles and managing risk to leveraging on-chain metrics and advanced technical analysis. Learn how to:
<ul>
<li>Decode market phases and spot key indicators

</li><li>Build and balance a resilient crypto portfolio

</li><li>Identify high-potential assets before they break out

</li><li>Design and implement your own automated trading systems

</li><li>Grasp Bitcoin’s central role in the evolving crypto landscape



Clear, practical, and thoroughly resourced, this is the guide the author wishes they had at the beginning of their journey. Now it’s yours—to help you make smarter decisions, avoid costly mistakes, and grow your investments with clarity and conviction.
</li></ul>

How to Analyze, Select and Manage Digital Assets

Investing in Crypto with Confidence

This open access book assesses whether European data regulation can be amended in light of contemporary technological developments. In an era when data powers our daily lives, economies and societies, data regulation is essential. However, European data regulation is still premised on concepts and foundations that were developed more than 50 years ago. The book offers an in-depth exploration of the European data regulatory landscape, from its historical roots to the challenges posed by new technological advancements. Through a detailed legal and technical analysis, it explores key data categories - such as anonymised, pseudonymised, aggregated, sensitive data, and metadata - highlighting their fluid and changing nature and the growing possibilities for transitioning between them. By identifying regulatory tensions and challenges arising from various technologies, such as AI, Big Data, and quantum computing, the book offers policymakers, legal scholars, computer scientists and data protection experts different perspectives on how to reshape future privacy and data protection legislation in a rapidly advancing technological world. The ebook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com.

The Past, Present, and Future of European Data Regulation

Whether you want to criticise, kill, or use AI, you have to get through the hype and uncover the real story. Start with labour: in automation theory, a centaur is a person who chooses to use technology to help them do the things that matter to them. A reverse centaur is a person who has been conscripted to serve as a helper for a machine, at an inhuman, machine pace: a driver made to deliver all day long, nonstop; a warehouse worker made to work without food or bathroom breaks; a programmer made to crank out impossible amounts of code. As Doctorow says: it’s not enough to ask what the technology does – we have to understand who it’s doing it for and who it’s doing it to. The intended audience for AI hype isn’t the people who are forced to use AI. The AI show is a performance staged for bosses and investors. . Investment bankers claim AI will to be worth more than $16 trillion: a number that only makes sense if AI replaces vast swathes of the wage-earning human workforce. To justify that level of "value," every story about AI must be presented as inevitable, world-changing disruption. Even the tales of the robot apocalypse are a calculated attempt to bolster the fearsome power of AI. Anything that can’t go on forever eventually stops. When the AI bubble bursts, what will we salvage? Is there something in the wreckage that everyday people will find useful? In The Reverse Centaur’s Guide to Life After AI - as he so successfully did in Enshittification - Doctorow recounts both how we found ourselves in this dire situation and how we can get through it, to a life "after" AI in which the tools work for us, not the other way around.

How to Think About Artificial Intelligence Before It's Too Late

The Reverse Centaur's Guide to Life After AI

Studieren, aber richtig

Künstliche Intelligenz sinnvoll in den wissenschaftlichen Schreibprozess zu integrieren, ohne dabei die Verantwortung für den eigenen Text abzugeben – wie das gelingt, zeigt Isabella Buck in ihrem Buch. 
Sie erklärt Begrifflichkeiten und Funktionsweisen und geht auf Herausforderungen bei der Anwendung, wie ethische und datenschutzrechtliche Aspekte, ein. Anschließend erläutert sie verschiedene Nutzungsmöglichkeiten von generativer KI beim wissenschaftlichen Schreiben und zeigt, wie Prompting gelingen kann. In der zweiten Auflage hat sie neueste wissenschaftliche Studien integriert und das Kapitel über Prompting um einen Abschnitt zum Context Engineering ergänzt.
Ein aufschlussreiches Buch für Studierende mit erster Erfahrung im wissenschaftlichen Schreiben und Promovierende aller Fachrichtungen.

Wissenschaftliches Schreiben mit KI

Recursions

A Media Theory of Machine Learning

Errant Intelligence

Edge AI is transforming everyday devices by putting intelligence where it matters most: directly inside the hardware. With on-device inference, a camera can recognize a visitor instantly, a phone can translate speech without streaming audio to the cloud, and a wearable can detect anomalies in real time-fast, private, and reliable even when the network disappears.This book is your practical guide to building exactly those kinds of systems with the Raspberry&nbsp;Pi AI&nbsp;HAT+ and the Hailo-8L accelerator. You'll start with clear foundations: core&nbsp;AI and machine-learning concepts, how neural networks work, and what truly distinguishes Edge&nbsp;AI from cloud AI-plus an honest look at ethical considerations and future impacts.Then it's straight to hands-on physical computing. Step by step, you'll set up Raspberry&nbsp;Pi&nbsp;OS, power and cooling, and develop in Python using the Thonny&nbsp;IDE. You'll learn GPIO basics with lights and servos, mount the AI&nbsp;HAT+ hardware, install and verify the Hailo software stack, and connect the right camera-official modules or USB webcams, even multiple cameras.From your first pipeline to real projects, you'll run person detection, pose estimation, segmentation, and depth estimation, then level up with YOLO object detection: smart alerts, guest counters, and custom extensions. You'll even connect vision to motion by combining gesture recognition with servo-driven mechanisms, including a robotic arm.With troubleshooting tips, hardware essentials, and a practical Python refresher, this book turns Edge&nbsp;AI from buzzword into buildable reality.

AI Projects for the Raspberry Pi with the AI HAT+

Edge AI Made Practical

Modern Trends In Financial Engineering

Multiscale Financial Data Analytics and Machine Learning offers a systematic and comprehensive study on the multiscale approach to financial data analytics and machine learning. This book covers an array of multiscale methods to discover the properties of various timescales embedded in a financial time series, including noise-assisted empirical mode decomposition methods. Important interpretable multiscale outputs from the estimation are recognized as a new set of features that can be used for machine learning. The feature selection problem for machine learning is examined in this volume.This book offers an applied quantitative approach that combines novel analytical methodologies and practical applications to a wide array of examples with real-world data. It is self-contained and organized in its presentation. The explanations of the methodologies are both accessible and detailed enough to capture the interest of the curious student or researcher. Step-by-step descriptions of the algorithms are provided for straightforward implementation.

Multiscale Financial Data Analytics And Machine Learning

How the rise of AI agents--and other forms of autonomous intelligence--will transform every aspect of how companies create value and compete.Companies have long operated with a basic assumption: intelligence is scarce. Talent is limited, expertise is expensive, and good judgment is hard to scale. But that world is ending.AI agents are bringing a new form of labor into the enterprise--one that can work autonomously, learn continuously, and scale instantly. Their embodied counterparts, from drones to humanoid robots, are doing the same in the physical world. Together, these systems are introducing a new economic reality: cognition is becoming cheap, elastic, and abundant.In Abundant Intelligence, Deloitte's Nitin Mittal and futurist Mike Walsh show what happens when intelligence becomes cheap and widely available. Drawing on inside access to the people leading AI transformations at the world's most powerful companies, they uncover how this shift is challenging every assumption about strategy, productivity, and leadership, and what organizations must do now to stay ahead.As abundance becomes the new normal, the leader's job shifts from collecting intelligence to directing it. Those who learn to harness this expanding workforce of digital labor will unlock new levels of speed, creativity, and advantage. For everyone else, the gap will widen fast.

How Digital Labor Will Rewrite the Rules of Business

Abundant Intelligence

Cut through the hype. Master the basics. Transform your work

How to AI

Routledge Studies in Innovation, Organizations and Technology

In an era where artificial intelligence is transforming industries, this book focuses on the pivotal role AI plays in talent acquisition and workforce engagement. It brings together insights from leading scholars to demonstrate how AI enhances recruitment processes, improves employee retention, and revolutionizes workforce management, ultimately reshaping the future of work.The book offers a comprehensive examination of how AI can be effectively leveraged to identify top talent, streamline hiring processes, and foster employee engagement through personalized experiences. International contributors offer both theoretical frameworks and practical applications of AI in recruitment and retention, illustrated with real-world examples, case studies, and cutting-edge research. From optimizing hiring strategies to engaging the workforce more effectively, this book provides actionable insights that bridge academic research and industry practices.Aimed at scholars and astute professionals, particularly in the fields of human resources, business management, and organizational development, this book is an essential guide for those who want to stay ahead in the rapidly evolving world of AI-driven workforce management. By understanding and implementing AI strategies, readers can enhance their organization's talent acquisition and retention capabilities, fostering a more dynamic and engaged workforce.

Enhancing Workforce Engagement

Talent Acquisition and AI

In Digitizing the Supply Chain, Nick Seiersen explores the transformative potential of information technologies in modern supply chain management. This book examines the foundational technologies, tools, and challenges of the digital transformation of supply chains, offering insights into future trends and opportunities.

The author reviews key technologies such as AI, IoT, blockchain, and Big Data, illustrating their application through real-world case studies. Readers will gain a practical understanding of how to leverage these technologies to optimize logistics, enhance cybersecurity, and manage risk.

This book serves as an essential resource for executives and professionals seeking to navigate the complexities of deploying new technologies to build resilient, future-proof supply chains.

How AI and 8 Technology Building Blocks Can Supercharge Your Supply Chain

Digitizing the Supply Chain

Developments and Advances in the Supply Chain Industry

Digital Transformation in Retail Supply Chain Management for Logistics 5.0 explains how these technologies are reshaping retail supply chain management. The book elucidates on the digital tools and strategies organizations can employ to optimize their retail supply chain management, minimize costs, enhance customer satisfaction, and achieve sustainability objectives through industry 5.0-enabled technologies. It innovatively blends the details of recent advancements across retail supply chains and supply chain-related digital transformations. Its cutting-edge perspective makes it an invaluable asset for industry professionals, policymakers, business owners, managers, researchers, practitioners, academicians, instructors, and students in retail, logistics supply chain management, digital business, and innovation. The book explores the nuances of the Supply Network 5.0, discussing the synergy between humans and machines, especially in the context of robotic process automation systems and artificial intelligence tools in the "new normal" of retail supply chain management. In addition, it specifically addresses textile products, FMCG, online products, construction, food and beverages, the shoe industry, SMEs, and other manufacturing sectors. Other sections delves into the often-overlooked environmental sustainability ramifications of the Fifth Industrial Revolution.

Digital Transformation in Retail Supply Chain Management for Logistics 5.0

AI in the Financial Markets

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