Über uns

À propos de nous

Open Access

Karriere

Carrière

Aboverträge Kündigen

Résiliation d’abonnement

Vertrag widerrufen

Résiliation de contrat 

Datenschutz

Protection des données

Impressum

Mentions légales

Barrierefreiheit

Accessibilité

Zahlung und Lieferung

Paiement et livraison

Libra

Was ist Libra?

C'est quoi Libra ?

Kostenlos testen

Tester gratuitement

LEXIA

LEXIA Arbeitsrecht

Was ist LEXIA?

C'est quoi LEXIA ?

LEXIA Familienrecht

Zeitschriften

Revues

recht

Pflegerecht

ZBJV

forumpoenale

ZStrR

Anwaltsrevue

Revue de l'avocat

RSAS

FamPra.ch

ASYL

Life Science Recht

BlAR

Sachbuch

Livres spécialisés

LOKI

Semaphor

Fokusthemen

Focus

Thema

Recht studieren

Arbeitsrecht

Droit du travail

Studium

Études

Familienrecht

Droit de la famille

Sozialversicherungsrecht

Droit des assurances sociales

Strafrecht

Droit pénal

Aktienrecht

Droit des sociétés anonymes

Persönlichkeitsrecht

Droit de la personnalité

Publikationen

Publications

Literatur

Digitales Angebot

Bücher

Livres

Buchreihen

Collections

Onlinemodule LEXIA

Modules en ligne LEXIA

recht.ch

Studienliteratur

Littérature pour les études

Swisslex

Dienstleistungen

Services

Dienstleistungen für

Corporate Books

Publishing Lösungen

Aktuelles

Geschäftskunden

Professionnels

Corporate Publishing

Content solutions

Buchhandlungen

Librairies

Veranstaltungen

Événements

Presse

Dozierende

Enseignants

Studierende

Étudiants

Inserierende

Annonceurs

Newsletter

Blog

Autorinnen/Autoren

Auteurs

Unsere Schreibenden

Hilfe

Unsere Autorinnen und Autoren

Liste

Autorenlounge

Espace des auteurs

Bei uns publizieren

Publier chez nous

Open Access Policy

Verlag

Éditions

Themen

Mehr wissen

Mitarbeitende

Collaborateurs

Geschichte

Histoire

Unser Magazin

Notre magazine

Vision und Mission

Vision et mission

Partner

Partenaires

Unternehmenskultur

Culture d'entreprise

Kontakt

Contact

Shop

Schweizer Recht

Ausländisches Recht

Über unseren Shop

Neuerscheinungen

Nouveautés

Sortiment & Suche

Catalogue & Recherche

Vorankündigungen

À paraître

Nach Rechtsgebiet

Par domaine juridique

Kommentare

Commentaires

Gesamtkatalog

Catalogue complet

Fachkatalog Recht

Catalogue de droit

Produkt vom BFSG ausgenommen: Hersteller ist Kleinstunternehmen

Ajay Agrawal

Joshua Gans

Avi Goldfarb

Máquinas predictivas

La sencilla economía de la inteligencia artificial

PREDICCIÓN. La magia de las máquinas predictivas. ¿Por qué se llama inteligencia?. Los datos son el nuevo petróleo. La nueva división del trabajo. TOMA DE DECISIONES. Descifrando decisiones. El valor del juicio. Prediciendo el juicio. Dominar la complejidad. Toma de decisiones totalmente automatizada. HERRAMIENTAS. Deconstruir los flujos de trabajo. Descomponiendo las decisiones. Rediseñando el trabajo. ESTRATEGIA. La IA y los directivos de alto nivel. Cuando la IA transforma tu negocio. Su estrategia de aprendizaje. Gestionar el riesgo de la IA. SOCIEDAD. Más allá del negocio.

Chapman & Hall/CRC Texts in Statistical Science

From Alan Turing breaking the Enigma code to ChatGPT reshaping how we work and create, artificial intelligence has always been powered by a single unifying principle: learning from data under uncertainty. This book reveals the mathematical machinery behind modern AI, weaving together Bayesian probability, statistical learning, and deep neural networks into a coherent intellectual framework. Whether you seek to understand why large language models hallucinate, how recommendation systems predict your preferences, or what makes reinforcement learning agents master complex games, this book equips you with both the theoretical foundations and practical intuitions that define the modern AI playbook.Key Features:<ul> <li>Builds Bayesian reasoning from first principles through historical examples like submarine search and WWII code-breaking</li> <li>Bridges classical statistics and deep learning, connecting linear regression to transformers</li> <li>Covers the complete AI stack: probability, decision theory, Gaussian processes, neural networks, CNNs, NLP, and LLMs</li> <li>Emphasizes uncertainty quantification-building systems that know what they don't know</li> <li>Practical applications across finance, healthcare, operations, and autonomous systems</li> <li>Emerging topics: AI agents, RLHF, and retrieval-augmented generation</li> </ul>Written for graduate students, data scientists, and quantitatively-minded practitioners, this book assumes comfort with calculus and basic probability while building sophisticated intuitions progressively. Business analysts will appreciate the decision-theoretic framing; engineers will value the architectural insights; researchers will find rigorous foundations for further study. Whether used as a course textbook, professional reference, or intellectual companion for understanding the AI revolution transforming every industry, this book delivers the rare combination of mathematical depth and accessible exposition that makes complex ideas genuinely understandable.

Foundations of Data Science

Bayes, AI, and Deep Learning

This book presents a comprehensive and integrated framework for managing market and liquidity risk in trading and investment portfolios. By combining theoretical rigor with machine learning-driven modeling and empirical validation, it addresses a critical gap in current financial literature: the joint modeling of interdependent risk dimensions through advanced data science techniques.The book bridges the divide between academic theory and real-world practice, demonstrating how machine learning can be systematically applied to model complex risk behaviors, capture regime shifts, and improve portfolio resilience. Traditional risk frameworks often struggle to handle nonlinear, high-dimensional, and heavy-tailed market dynamics. In contrast, this book integrates ML-based optimization techniques—covering liquidity proxies, price impact models, Liquidity-Adjusted Value-at-Risk (LVaR), and regime-switching volatility structures—to offer a more adaptive and robust risk management paradigm. Each chapter offers a balance of quantitative depth and application-oriented insight, enabling readers to connect rigorous research with day-to-day decision-making in risk and portfolio management.Mazin A. M. Al Janabi
 is a distinguished scholar and practitioner in finance, banking, and financial engineering with more than three decades of experience spanning science, technology, and academia. He holds a PhD in Nuclear Engineering from the University of London (UK) and has held senior management roles at ING-Barings and BBVA, including Director of Global Market Risk Management and Head of Trading Risk. A Full Research Professor, he has served at leading institutions such as EGADE Business School (Mexico), United Arab Emirates University, and Al Akhawayn University (Morocco). His research, published in top-tier journals including the 
 European Journal of Operational Research
 , 
 International Review of Financial Analysis
 , and 
 Annals of Operations Research
 , explores market and liquidity risk in both emerging and developed markets. Prof. Al Janabi is also the developer of the “Al Janabi Model” for Liquidity Risk Management, recognized in academic literature for its innovation. As a research fellow at the Economic Research Forum (ERF) and a frequent keynote speaker, he continues to shape contemporary discourse in proprietary trading, market liquidity, and financial risk analytics.

A Unified Machine-Learning-Compatible Framework for Proprietary Trading, Portfolio Management, and Financial Stability

Quantitative Market and Liquidity Risk Analytics

Environmental Intelligence in Sustainable Hospitality Operations provides a comprehensive, accessible, and data-led approach for achieving sustainability through the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) across hospitality operations.The volume explains how smart sensors, real-time environmental monitoring, predictive analytics, and intelligent automation can optimize energy and water consumption, reduce food and material waste, enhance indoor air quality, and support carbon reduction strategies in hotels, resorts, restaurants, and allied tourism services. Chapters introduce practical frameworks for designing and implementing smart sustainable systems, including digital dashboards, AI-enabled decision models, and performance indicators aligned with environmental, social, and governance (ESG) requirements, supported with international applied case studies throughout. The book also addresses critical implementation issues such as data management, ethics, cybersecurity, investment justification, and organizational readiness.By combining environmental science with hospitality innovation, this innovative and timely book offers a comprehensive guide for researchers, students, industry professionals, and policymakers seeking scalable pathways toward low-carbon, resource-efficient, and resilient hospitality operations.

AI and The Internet of Things Implications

Environmental Intelligence in Sustainable Hospitality Operations

Law and Practical Reason

Moral Responsibility and Artificial Intelligence

Shortlisted for the Financial Times and Schroders Business Book of the Year Award How 1,000 years of global history show why technological and economic progress is often followed by stagnation and even collapse In How Progress Ends, Carl Benedikt Frey challenges the conventional belief that economic and technological progress is inevitable. For most of human history, stagnation was the norm, and even today progress and prosperity in the world's largest, most advanced economies--the United States and China--have fallen short of expectations. To appreciate why we cannot depend on any AI-fueled great leap forward, Frey offers a remarkable and fascinating journey across the globe, spanning the past 1,000 years, to explain why some societies flourish and others fail in the wake of rapid technological change. By examining key historical moments--from the rise of the steam engine to the dawn of AI--Frey shows why technological shifts have shaped, and sometimes destabilized, entire civilizations. He explores why some leading technological powers of the past--such as Song China, the Dutch Republic, and Victorian Britain--ultimately lost their innovative edge, why some modern nations such as Japan had periods of rapid growth followed by stagnation, and why planned economies like the Soviet Union collapsed after brief surges of progress. Frey uncovers a recurring tension in history: while decentralization fosters the exploration of new technologies, bureaucracy is crucial for scaling them. When institutions fail to adapt to technological change, stagnation inevitably follows. Only by carefully balancing decentralization and bureaucracy can nations innovate and grow over the long term--findings that have worrying implications for the United States, Europe, China, and other economies today. Through a rich narrative that weaves together history, economics, and technology, How Progress Ends reveals that managing the future requires us to draw the right lessons from the past.

Technology, Innovation, and the Fate of Nations

How Progress Ends

Decision-Making in the Age of Artificial Intelligence

Do We Still Need to Decide?

The new book from the acclaimed author of Number Go Up.

Scam World

Tech, War and the Fight for Humanity

Thundercloud

Foundations for Decision-Focused Regularized Learning

Operational Data Analytics

Platform Supply Chains in the AI Era

This open access book provides a systematic and in-depth analysis of the critical risks inherent in modern platform-based supply chains. Employing rigorous analytical methods, including game theory and advanced, computationally efficient simulation techniques, it delves into three core areas: operational risks, information and data risks, and quality and compliance risks. The book moves beyond traditional supply chain paradigms to address challenges unique to the platform economy. This includes the strategic threat of platforms using seller data to launch competing products, the complex trade-offs in managing third-party product quality, the impact of reactive capacity on quality decisions, and the challenge of optimizing inventory across networks of unprecedented scale. It is an essential resource for graduate students, academic researchers, and advanced practitioners in the fields of operations management, supply chain management, and information systems. The content is suitable for readers with a graduate-level understanding of these disciplines.

Risk Management

Platform Supply Chains 5

Theory and Lessons from Leading Companies

AI-Powered Functions

Máquinas predictivas

Autres titres sur ce thème