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Morgan C: Formal Methods, Informally

Formal Methods, Informally

How to Write Programs That Work

Bloomsbury Handbooks

The Bloomsbury Handbook of LGBTQIA+ Inclusion in Educational Contexts brings together international contributions in scholarship and coverage, mapping the discipline through theoretical explorations, personal narratives and empirical studies. The handbook focuses on themes that examines Lesbian, Gay, Bisexual, Transgender, and Queer issues including: inclusion in action, engaging teaching spaces, social justice standpoints, student/teacher agency, preservice teacher education, criticality in educative spaces and children and agency. The book provides a crucial lens into educational contexts that fuel or hinder human flourishing, the power of learning spaces and institutional educative standpoints and teaching approaches. Cultural, social and economic injustices that perpetuate cycles of disadvantage and oppressive narratives are explored using different theoretical frameworks that underpin equitable and inclusive educative landscapes.

The Bloomsbury Handbook of Lgbtqia+ Inclusion in Educational Contexts

Where to Go and What to Study

The Times Good University Guide 2027

A Critical Introduction to International Relations

World Politics

This book illustrates statistics with the R programming language, an emerging tool in data science. Filled with techniques for data science and analytics programming, the book is written for students and professionals. It is focused on learning outcomes and problem solving.

Demystifying Probability and Statistics for Data Scientists with R

Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially, however, the abundance of resources can be overwhelming

Using SAS Enterprise Miner

Data Science and Machine Learning for Non-Programmers

Bloomsbury Writer's Guides and Anthologies

A Writer's Guide and Anthology

Short-Form Creative Writing

Modern Business Ethics

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

Chapman & Hall/CRC Studies in Informatics Series

Presenting first-order and propositional methods as well as implementation issues, this book provides a state-of-the-art introduction to the automation of logic. It focuses on superposition calculus and related rewriting techniques. It also covers decision procedures for certain theories and includes real-world applications. Along with the relevant theory, each chapter contains implementation methods, historical background, suggestions for further reading, and software. Supplemental materials and resources are provided on the book's website and a solutions manual is available for qualifying instructors.

Automation of Logic

Digital Transformation and Equitable Global Health: A Future-Ready Perspective presents a collective body of knowledge and global experiences that demonstrate current status and future trends in the use of exponential technologies and their potential for poverty reduction, improving health outcomes, strengthening health systems, and transforming traditional development aid structures. The book uses a translational innovation perspective to guide the reader-regardless of their area of expertise-on the rationale behind the co-creation of human-centered, affordable, and sustainable digital solutions. It addresses the interest of professionals from multiple areas (e.g., technology, health, social development, global financing), and it is a valuable resource for professionals, social scientists, practitioners, researchers, instructors, and undergraduate and graduate students interested in understanding the challenges and complexities of global public health and the applied uses of health technologies for equitable access to primary health care and universal health coverage.

A Future-Ready Perspective

Digital Transformation and Equitable Global Health

Fundamentals and Applications

Quantum Physics

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

Formal Methods, Informally

Informations bibliographiques

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Informations bibliographiques

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