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Sidoruk P: From Data to Dollars

From Data to Dollars

Getting started with Data Analytics and AI in Startups

Understand How to Use Artificial Intelligence in Your HR Role

AI for People Professionals

SDG - Forschung, Konzepte, Lösungsansätze zur Nachhaltigkeit

Nachhaltigkeit ist mehr als nur ein Trend – sie ist eine Notwendigkeit, auch im Software-Engineering und in der Künstlichen Intelligenz. Dieses Buch beleuchtet umfassend die Dimensionen nachhaltiger Softwareentwicklung – von ressourcenschonenden Architekturen über effiziente Programmiersprachen bis hin zur Optimierung von Rechenzentren und KI-Trainingsprozessen und ordnet diese in den Kontext der UN Sustainability Development Goals (SDG) ein. Praxisnahe Fallbeispiele zeigen, wie Unternehmen langfristige, wirtschaftlich und ökologisch sinnvolle Lösungen umsetzen können. Neben technischen Aspekten werden auch unternehmerische und gesellschaftliche Perspektiven betrachtet, um ein ganzheitliches Verständnis für nachhaltige Digitalisierung zu schaffen. Ein unverzichtbarer Leitfaden für alle, die Software verantwortungsvoll entwickeln und nutzen möchten.
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Wie Softwareentwicklung Investitionen und Zukunft sichert

Nachhaltiges Software-Engineering

Human Factors in Design, Engineering, and Computing

Modern Technologies in Ergonomics and Workplace Safety

Synthesis Lectures on Technology and Health

<div>This book provides a comprehensive overview of palliative care digital health by covering current developments, methodology, clinical relevance, research priorities, ethical issues, and policy related to technological innovations for those with serious illness. This type of book does not currently exist in the literature, as previous work primarily focuses on digital health for early identification of disease and facilitating self-care or ‘aging in place’ practices. This book addresses the lack of focus on digital health for people with palliative care needs. This book has a special focus on the needs of individuals as their health worsens throughout their illness. Consequently, the reader will benefit from this book’s focus on the science, methodology, application, and practicality of digital health developments in palliative care.</div>
<div>This book explores the barriers that prevent the meaningful use of digital health in palliative care, including expenses, interoperability issues, data privacy and security concerns, lack of effectiveness and equity, and the concern that technology may reduce face-to-face consultations between patients and clinicians. There is an overall lack of consensus about digital health research priorities in palliative care, and a lack of theories about how these technologies might improve care outcomes. Therefore, this book emphasizes the importance of identifying, discussing, and debating how technological innovations can be meaningfully used to ensure that frail people have appropriate access to palliative care services. Consequently, this book begins the conversation about articulating digital health research priorities in palliative care to determine how finite resources should be allocated to a field saturated with rapidly developing innovation.</div>

Technologies in Palliative Care for Older People

Das Handbuch leistet eine erste Bestandsaufnahme der im Fach Medienwissenschaft genutzten Methoden zur Untersuchung digitaler Kulturen. Es vermittelt einen Überblick über medienkulturwissenschaftliche Forschungsdesigns und den Umgang mit Forschungsdaten. Dabei stellt das Handbuch sowohl methodische Ansätze zur Erhebung und Analyse digitaler Artefakte, Praktiken und Phänomene vor, wie auch spezifisch digitale Methoden der Datenanalyse und -visualisierung. Die Beiträge stellen konkrete Anwendungen vor und reflektieren den jeweiligen methodischen Ansatz in der Fachkultur und den Arbeitsgebieten der Medienwissenschaft.

Handbuch Digitale Medien und Methoden

Advanced Intelligence Methods for Data Science and Optimization covers the latest research trends and applications of AI topics such as deep learning, reinforcement learning, evolutionary algorithms, Bayesian optimization, and swarm intelligence. The book is a comprehensive guide that provides readers with theoretical concepts and case studies for applying advanced intelligence methods to real-world problems. Authored by a team of renowned experts in the field, the book offers a holistic approach to understanding and applying intelligence methods across various domains. It explores the fundamental concepts of data science and optimization, providing a strong foundation for readers to build upon, and will be a welcomed resource for AI researchers, data scientists, engineers, and developers on key topics such as evolutionary optimization techniques, reinforcement learning, Natural Language Processing, Bayesian optimization, advanced analytics for large-scale data, fuzzy logic, quantum computing, graph theory, convex optimization, differential evolution, and more.

Advanced Intelligence Methods for Data Science and Optimization

This companion volume to Artificial Intelligence: A Guide for Everyone offers a comprehensive exploration of AI analytics, catering to individuals of all backgrounds and expertise levels. It seeks to demystify AI analytics by exploring core concepts, explaining various stages (Descriptive, Diagnostic, Predictive, and Prescriptive), and highlighting their limitations. Through domain-specific applications, it illustrates how AI is utilized across industries for innovation and efficiency, providing dedicated subsections for healthcare, finance, customer support, and more.Artificial Intelligence: Analytics, Platforms, and Risks thoroughly examines the AI infrastructure and ecosystem, offering insights into frameworks, platforms, tools, key players, and the critical hardware and software components supporting AI applications. It also addresses the multifaceted risks and challenges of AI, such as bad data, model selection bias, job displacement, weaponization, and ethical dilemmas, along with strategies to mitigate these risks.&nbsp;Additionally, it discusses the hurdles in AI adoption, including roadblocks, myths, planning complexities, resource requirements, and data and model challenges. Looking ahead, the book explores the future of AI, highlighting catalysts for technological progress, the transformative impact across industries, and emerging trends shaping the field. With the aim of empowering readers to navigate the complexities of AI, harness its potential, and contribute to its responsible and ethical advancement, this book serves as a comprehensive guide to AI technologies.

This companion volume to Artificial Intelligence for Everyone offers a comprehensive exploration of AI analytics, catering to individuals of all backgrounds and expertise levels. It seeks to demystify AI analytics by exploring core concepts, explaining various stages (descriptive, predictive, prescriptive), and highlighting their limitations. Through domain-specific applications, it illustrates how AI is utilized across industries for innovation and efficiency, providing dedicated subsections for healthcare, finance, customer support, and more.Artificial Intelligence: Analytics, Platforms, and Risks thoroughly examines the AI infrastructure and ecosystem, offering insights into frameworks, platforms, tools, key players, and the critical hardware and software components supporting AI applications. It also addresses the multifaceted risks and challenges of AI, such as bad data, model selection bias, job displacement, weaponization, and ethical dilemmas, along with strategies to mitigate these risks. Additionally, it discusses the hurdles in AI adoption, including roadblocks, myths, planning complexities, resource requirements, and data and model challenges. Looking ahead, the book explores the future of AI, highlighting catalysts for technological progress, the transformative impact across industries, and emerging trends shaping the field. With the aim of empowering readers to navigate the complexities of AI, harness its potential, and contribute to its responsible and ethical advancement, this book serves as a comprehensive guide to AI technologies.

Artificial Intelligence: Analytics, Platforms, and Risks

Precarious Futures&nbsp;explores the evolving and emerging relationship between crime and technology in an increasingly complex and interconnected world, along with its implications for new perceptions of crime and deviance. It evaluates the rise of the World Wide Web and the model of cybercrime, questions whether existing criminological thought offers relevance and efficacy in current circumstances, conditions and future predictions, and revisits the concept of Relative Deprivation and&nbsp;the underpinning social psychological and socio-political foundations of it. It argues that&nbsp;Relative Deprivation&nbsp;allied to post-industrial precarity provides a central platform for understanding crime and deviance in a hyper-connected and hyper-commercial neoliberal world.&nbsp;The book develops to explore current criminological and security conceptions of artificial intelligence, big data, crime and social control, as well as hacktivism, and how opportunities for crime have become ‘democratised’ and expanded through the Web. Drawing&nbsp;on empirical data, theoretical narratives and a review of the state of crime now and in a speculative near future, Hamerton and Webber discuss some potential directions for a new transdisciplinary critical criminology.&nbsp;Precarious Futures&nbsp;speaks to&nbsp;criminologists, sociologists and social theory scholars and students, as well as academics and professionals in associated technological fields such as cyber-security, computer science and web science.Christopher Hamerton&nbsp;is&nbsp;Deputy Director of the Institute of Criminal Justice Research at the&nbsp;University of Southampton, UK.Craig Webber&nbsp;is&nbsp;Head of the Department of Sociology, Social Policy and Criminology at the&nbsp;University of Southampton, UK.

Precarious Futures
 &nbsp;explores the evolving and emerging relationship between crime and technology in an increasingly complex and interconnected world, along with its implications for new perceptions of crime and deviance. It evaluates the rise of the World Wide Web and the model of cybercrime, questions whether existing criminological thought offers relevance and efficacy in current circumstances, conditions and future predictions, and revisits the concept of Relative Deprivation and&nbsp;the underpinning social psychological and socio-political foundations of it. It argues that&nbsp;Relative Deprivation&nbsp;allied to post-industrial precarity provides a central platform for understanding crime and deviance in a hyper-connected and hyper-commercial neoliberal world.&nbsp;The book develops to explore current criminological and security conceptions of artificial intelligence, big data, crime and social control, as well as hacktivism, and how opportunities for crime have become‘democratised’ and expanded through the Web. Drawing&nbsp;on empirical data, theoretical narratives and a review of the state of crime now and in a speculative near future, Hamerton and Webber discuss some potential directions for a new transdisciplinary critical criminology.&nbsp;
 Precarious Futures
 &nbsp;speaks to&nbsp;criminologists, sociologists and social theory scholars and students, as well as academics and professionals in associated technological fields such as cyber-security, computer science and web science.

Crime, Technology and the Web

Precarious Futures

Harnessing Artificial Intelligence to Ensure Diverse Global Teams

Dieses Buch bietet einen praxisnahen Einblick für Führungskräfte, Entscheider und Data-Science-Interessierte, die das Potenzial von Daten im Unternehmen voll ausschöpfen wollen. Es zeigt, wie Data Science nicht nur operative Prozesse optimiert, sondern auch strategisch zum langfristigen Geschäftserfolg beiträgt und neue Chancen erschließt. Basierend auf dem Podcast „Data Science mit Milch und Zucker“ behandelt das Buch zentrale Themen wie Datenstrategie, Künstliche Intelligenz, MLOps, Data Mesh und Business Impact. Es liefert konkrete Handlungsempfehlungen und echte Einblicke aus der Praxis – von der erfolgreichen Integration von Data Science bis zur effektiven Skalierung datengetriebener Projekte. Leserinnen und Leser erhalten wertvolle Best Practices führender Unternehmen, die den Wandel aktiv gestalten und datengetriebene Entscheidungen als Wettbewerbsvorteil nutzen. Ergänzt wird dies durch inspirierende Denkanstöße und sofort umsetzbare Impulse für den unternehmerischen Alltag.Für wen ist dieses Buch? Für Manager:innen, Unternehmer:innen, Data-Science-Verantwortliche und Changemaker, die datenbasiert entscheiden und ihre Organisation zukunftsfähig aufstellen wollen.Die Herausgebenden Prof. Dr. René Brunner ist Professor für Data Science, mehrfach ausgezeichneter Wissenschaftler, gefragter Speaker und Gründer der Datamics GmbH. Er lehrt an renommierten Universitäten im deutschsprachigen Raum, aktuell an der Hochschule Macromedia, und hat über 50.000 Menschen in Data Science ausgebildet. Seine Leidenschaft gilt der Verbindung von wissenschaftlicher Tiefe und praktischer Anwendung im Unternehmenskontext. Durch seine langjährige Erfahrung in Lehre, Forschung und Beratung kennt er die Herausforderungen und Erfolgsfaktoren datengetriebener Transformation aus erster Hand.Glorinda Matrone ist Data Strategin, Unternehmensberaterin und erfahrene Führungskraft im Digitalbereich. Mit fundierter Expertise begleitet sie Organisationen auf ihrem Weg zur Data-Driven Company und baut Brücken zwischen Technologie, Business und Menschen.

From Data to Dollars

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