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Chen P: Introduction to Foundation
Models

Introduction to Foundation Models

Develop the skills to stop AI-powered cyberattacks and leverage AI to improve your existing cybersecurity strategies.

Use AI to Protect Your Organization

Artificial Intelligence in Cybersecurity

Algorithms have become the key organizer through which power is enacted in our society. A huge amount of data regarding our daily routines are monitored and analyzed to make recommendations that manage, control, and lead our behaviors in everyday life. AI, Humans, and Misinformation: How Does AI Alter Human Behavior and How Do Humans Influence Algorithmic Misinformation? is a guide to understanding the dynamics of AI and misinformation in human contexts by addressing meaningful questions-How does AI alter human behavior and how do humans influence algorithmic decision-making? In answering these questions, this book examines the role of misinformation, disinformation, and fake news, and shows readers how to develop AI methods and algorithms that combat misinformation by using AI design choices that provide users and developers alike with meaningful control over AI. This book brings together various perspectives on algorithms into an integrated conceptual framework, and provides a broad socio-technical analysis, addressing critical and ethical issues of misinformation and fake news. The book offers a compelling insight into the misinformation phenomenon and the future of AI-based society. Readers will find an integrated technical analysis of the logic and social implications of algorithmic processes. Reporting from the cutting edge of critical technical methods and research, the result is useful and constructive for developing the relations between algorithms and humans. This is an imperative methodology for understanding what is at stake as industry and government use AI to reshape the world.

Decoding Bias, Algorithms, and Trust

Minds, Machines, and Misinformation

A story of unexpected love at the end of the world

Some Body Like Me

Understand the transformative impact of data and artificial intelligence on the global travel and tourism industry and how to leverage these innovations within travel businesses

Leveraging AI, Data and Analytics in Travel

Technology-Led Tourism

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

Discover the AI and data skills you'll need and develop your confidence to succeed in the digital age.

Gain the Confidence You Need to Succeed

Data and AI Skills

Intelligent IoT-based Diagnostic and Assistive Systems for Neurological Disorders

Ob in der Datenerfassung, der Fan-Interaktion, der Trainingssteuerung oder der Sportmedizin – überall sind die Auswirkungen von Digitalisierung und Innovation im sportlichen Kontext spürbar. Dieses Handbuch greift die spannende Schnittstelle zwischen Sportwissenschaft, Digitalisierung und Innovation auf und erläutert, wie innovative Technologien den Sport revolutioniert haben und zukünftig weiter revolutionieren werden.Inhaltlich wird ein umfassendes Spektrum an Themen behandelt, wie z. B. Innovationsmanagement, künstliche Intelligenz, maschinelles Lernen, Big Data-Analyse, Augmented Reality sowie Fallstudien und Praxisbeispiele mit Bezug zum Sport und zur Sportwissenschaft. Diese sind wiederum breitgefächert und umfassen beispielsweise die Sportlehrer*innenbildung, den Schulsport, den Alterssport, sowie den Vereins- und Profisport. &nbsp;Für Trainer*innen, Profisportler*innen, Manager*innen, Lehrkräfte, Wissenschaftler*innen, Studierende und Technologiebegeisterte ist dieses Handbuch daher ein unverzichtbares Nachschlagewerk, um erfolgreich im modernen Sportumfeld zu navigieren. Der HerausgeberProf. Dr. Daniel Memmert&nbsp;ist geschäftsführender Institutsleiter und Professor am Institut für Trainingswissenschaften und Sportinformatik an der Deutschen Sporthochschule Köln. Er ist Herausgeber und Autor zahlreicher Lehrbücher mit Arbeitsschwerpunkten in der Bewegungswissenschaft sowie in der Sportpsychologie und -informatik. Sein Institut organisiert zwei Zertifikatsstudiengänge (Spielanalyse Team Köln / Sportdirektor*in im Nachwuchsleistungs- und Amateurfußball) sowie den ersten internationalen Weiterbildungs-Masterstudiengang „Spielanalyse“.

Ob in der Datenerfassung, der Fan-Interaktion, der Trainingssteuerung oder der Sportmedizin – überall sind die Auswirkungen von Digitalisierung und Innovation im sportlichen Kontext spürbar. Dieses Handbuch greift die spannende Schnittstelle zwischen Sportwissenschaft, Digitalisierung und Innovation auf und erläutert, wie innovative Technologien den Sport revolutioniert haben und zukünftig weiter revolutionieren werden. Inhaltlich wird ein umfassendes Spektrum an Themen behandelt, wie z. B. Innovationsmanagement, künstliche Intelligenz, maschinelles Lernen, Big Data-Analyse, Augmented Reality sowie Fallstudien und Praxisbeispiele mit Bezug zum Sport und zur Sportwissenschaft. Diese sind wiederum breitgefächert und umfassen beispielsweise die Sportlehrer*innenbildung, den Schulsport, den Alterssport, sowie den Vereins- und Profisport. &nbsp;

Für Trainer*innen, Profisportler*innen, Manager*innen, Lehrkräfte, Wissenschaftler*innen, Studierende und Technologiebegeisterte ist dieses Handbuch daher ein unverzichtbares Nachschlagewerk, um erfolgreich im modernen Sportumfeld zu navigieren.

Handbuch Sport und Sportwissenschaft

Digitalisierung und Innovation im Sport und in der Sportwissenschaft

New Directions in Contemporary Art

The field of AI Art is a hotbed for strange, uneasy partnerships between big tech, big art and critical culture. Not since Walter Benjamin's Age of Mechanical Reproduction has there been a similar challenge to humanist art criticism. This book examines how a contemporary critic should best engage with, contextualise and effectively critique machine-learning-based art. In considering this question, Nora Khan looks at the rush of institutions to place AI Art within an art-historical lineage while they simultaneously accept significant funding from technology companies. She discusses the scale and speed at which technological production, machine learning, and AI have abraded the individual's capacity for critical evaluation, moving us to consider what a shared, collective criticism of AI might sound like.

The field of AI Art is a hotbed for strange, uneasy partnerships between big tech, big art and critical culture. Not since Walter Benjamin's Age of Mechanical Reproduction has there been a similar challenge to humanist art criticism. This book examines how a contemporary critic should best engage with, contextualise and effectively critique machine-learning-based art. In considering this question, Nora Khan looks at the rush of institutions to place AI Art within an art-historical lineage while they simultaneously accept significant funding from technology companies. She discusses the scale and speed at which technological production, machine learning, and AI have abraded the individual’s capacity for critical evaluation, moving us to consider what a shared, collective criticism of AI might sound like.

AI Art, Machine Learning and the Stakes for Art Criticism

Technology-Assisted Physical Gait Rehabilitation: How Robotics, Data Science, and Neuroscience are Changing Modern Physical Therapy delves into the integration of advanced computational modeling, robotic systems, data analytics, and neuroscientific principles to revolutionize physical gait therapy. This book addresses rehabilitation techniques for conditions like stroke, traumatic brain injury, and incomplete spinal cord injury, showcasing a multidisciplinary approach that brings together expertise from various domains. This comprehensive volume gathers insights from leading experts in robotics, human biomechanics, physical therapy, neuroscience, engineering, and medicine. It discusses current advancements and future directions in technology-assisted gait therapy, emphasizing the synergy of interdisciplinary collaboration to achieve breakthroughs in rehabilitation techniques. The book also highlights ongoing work and the potential developments necessary to foster significant progress in this field.

How Robotics, Data Science, and Neuroscience are Changing Modern Physical Therapy

Technology-Assisted Physical Gait Rehabilitation

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

Malware detection is exceedingly challenging, requiring deeper expertise in two domains: machine learning (ML) and malware analysis.This comprehensive collection guides ML practitioners and researchers into the state-of-the-art and underlying insights needed to work in and research problems at the intersection of machine learning and cyber security, particularly around the problem of malware targeting the Windows platform.This useful volume's contributions come from a range of experts, representing large companies, major universities, and government labs, all working at the frontiers of malware detection and remediation research.

Machine Learning For Malware Detection

Introduction to Foundation Models

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