Tag Archives: Foundations

Graph Neural Networks: Foundations, – Hardcover, by Wu Lingfei Cui – Acceptable

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Graph Neural Networks: Foundations, – Hardcover, by Wu Lingfei Cui – Acceptable

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Graph Neural Networks: Foundations – Hardcover by Wu Lingfei Cui – Acceptable

If you’re interested in diving deep into the world of Graph Neural Networks, then Wu Lingfei Cui’s book is a great place to start. This hardcover edition covers the foundational concepts of GNNs, making it perfect for both beginners and experienced researchers in the field.

Cui’s writing style is clear and concise, making complex topics easy to understand. The book covers everything from the basics of graph theory to advanced GNN models and applications. It also includes practical examples and case studies to help readers apply the concepts in real-world scenarios.

Overall, Graph Neural Networks: Foundations is a valuable resource for anyone looking to expand their knowledge of GNNs. Whether you’re a student, researcher, or industry professional, this book is sure to provide valuable insights and guidance in this rapidly evolving field.
#Graph #Neural #Networks #Foundations #Hardcover #Lingfei #Cui #Acceptable

Learning Machines: Foundations of Trainable Pattern Classifying Systems Nilsson

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Learning Machines: Foundations of Trainable Pattern Classifying Systems Nilsson

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Learning Machines: Foundations of Trainable Pattern Classifying Systems by Nils J. Nilsson

In this groundbreaking book, Nils J. Nilsson explores the foundations of trainable pattern classifying systems, also known as learning machines. Drawing on his extensive research and expertise in artificial intelligence, Nilsson delves into the theory and practical applications of these systems, shedding light on how they can be used to solve complex problems in a wide range of fields.

From the basics of pattern recognition to advanced machine learning algorithms, Nilsson covers it all in this comprehensive guide. Whether you’re a student, researcher, or practitioner in the field of artificial intelligence, this book is a must-read for anyone interested in understanding the inner workings of trainable pattern classifying systems.

With clear explanations, detailed examples, and insightful commentary, Learning Machines is a valuable resource for anyone looking to dive deep into the world of artificial intelligence and machine learning. Nilsson’s expertise and passion for the subject shine through in every chapter, making this book a must-have for anyone interested in the future of intelligent systems.
#Learning #Machines #Foundations #Trainable #Pattern #Classifying #Systems #Nilsson,machine learning

Foundations of IT Service Management Based on ITIL V3 (Spanish Management) (I…

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Foundations of IT Service Management Based on ITIL V3 (Spanish Management) (I…

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Fundamentos de Gestión de Servicios de TI Basados en ITIL V3 (Gestión Española) (Parte I)

En la actualidad, la Gestión de Servicios de TI se ha convertido en un pilar fundamental para las organizaciones que buscan mejorar su eficiencia y productividad en el uso de la tecnología de la información. En este sentido, ITIL (Information Technology Infrastructure Library) se ha posicionado como un marco de referencia ampliamente utilizado en todo el mundo para la gestión de servicios de TI.

En esta serie de publicaciones, abordaremos los fundamentos de la Gestión de Servicios de TI basados en ITIL V3, con un enfoque específico en la gestión de servicios de TI en el contexto español. En esta primera entrega, nos centraremos en los conceptos clave de ITIL V3 y su aplicación en el entorno empresarial español.

ITIL V3 se compone de cinco libros principales que abarcan los procesos, funciones y roles necesarios para la gestión de servicios de TI. Estos libros son:

1. Estrategia de Servicio
2. Diseño de Servicio
3. Transición de Servicio
4. Operación de Servicio
5. Mejora Continua de Servicio

Cada uno de estos libros proporciona una guía detallada sobre cómo planificar, diseñar, implementar, operar y mejorar los servicios de TI de una organización. En el contexto español, es fundamental adaptar estos conceptos y prácticas a las necesidades y particularidades del mercado local, teniendo en cuenta aspectos culturales, legales y regulatorios específicos.

En las próximas entregas de esta serie, profundizaremos en cada uno de los libros de ITIL V3 y exploraremos su aplicación en el entorno español. ¡No te pierdas la próxima entrega!
#Foundations #Service #Management #Based #ITIL #Spanish #Management #I.., Managed Services

Integration of Cloud Computing with Internet of Things: Foundations, Analytics a

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Integration of Cloud Computing with Internet of Things: Foundations, Analytics a

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nd Applications

Cloud computing and Internet of Things (IoT) are two rapidly evolving technologies that are transforming the way we interact with the digital world. The integration of these two technologies holds immense potential for enhancing efficiency, scalability, and flexibility in various industries.

In this post, we will explore the foundations, analytics, and applications of integrating cloud computing with IoT.

Foundations:
Cloud computing provides the infrastructure and resources needed to store, process, and analyze data generated by IoT devices. By leveraging the cloud, organizations can access virtually unlimited computing power and storage capacity, enabling them to handle the massive amounts of data generated by IoT devices in real-time.

Analytics:
One of the key benefits of integrating cloud computing with IoT is the ability to perform advanced analytics on the data collected from IoT devices. By utilizing machine learning and artificial intelligence algorithms, organizations can gain valuable insights from their IoT data, enabling them to make informed decisions and optimize their operations.

Applications:
The integration of cloud computing with IoT has numerous applications across various industries. In healthcare, IoT devices can be used to monitor patients’ vital signs and transmit data to the cloud for analysis by healthcare providers. In manufacturing, IoT sensors can be used to track inventory levels and equipment performance, with the data being processed in the cloud to optimize production processes.

Overall, the integration of cloud computing with IoT is revolutionizing the way we collect, analyze, and utilize data. By harnessing the power of these two technologies, organizations can unlock new opportunities for innovation and growth.
#Integration #Cloud #Computing #Internet #Foundations #Analytics, Cloud Computing

Cloud Computing Security : Foundations and Challenges, Hardcover by Vacca, Jo…

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Cloud Computing Security : Foundations and Challenges, Hardcover by Vacca, Jo…

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In this post, we will be discussing the book “Cloud Computing Security: Foundations and Challenges” by Jo Vacca. This comprehensive guide delves into the complex world of cloud computing security, exploring the fundamental principles and challenges that organizations face when securing their cloud environments.

Vacca provides a detailed overview of the foundations of cloud computing security, examining key concepts such as data protection, identity and access management, encryption, and compliance requirements. The book also addresses emerging trends and technologies in cloud security, including the use of artificial intelligence and machine learning to enhance threat detection and incident response.

One of the key challenges highlighted in the book is the shared responsibility model, which dictates that both cloud service providers and their customers are responsible for securing their data and applications in the cloud. Vacca offers practical advice on how organizations can navigate this complex landscape and implement effective security measures to protect their sensitive information.

Overall, “Cloud Computing Security: Foundations and Challenges” is a valuable resource for IT professionals, security practitioners, and business leaders looking to understand the intricacies of cloud security and develop a robust security strategy for their cloud deployments. Whether you are new to cloud security or looking to enhance your existing knowledge, this book is a must-read for anyone interested in safeguarding their data in the cloud.
#Cloud #Computing #Security #Foundations #Challenges #Hardcover #Vacca #Jo.., Cloud Computing

Foundations of Statistical Natural Language Processing by Christopher Manning

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Foundations of Statistical Natural Language Processing by Christopher Manning

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Foundations of Statistical Natural Language Processing by Christopher Manning is a comprehensive guide to the fundamental concepts and techniques of natural language processing (NLP). With a focus on statistical methods, this book provides a solid foundation for understanding how to analyze and process human language using computational tools.

In this book, Manning covers a wide range of topics, including language modeling, part-of-speech tagging, parsing, and information retrieval. He also discusses the use of machine learning algorithms and statistical techniques to build NLP systems that can understand and generate human language.

With its clear and concise explanations, Foundations of Statistical Natural Language Processing is an essential resource for students, researchers, and practitioners in the field of NLP. Whether you are new to the subject or looking to deepen your knowledge, this book offers valuable insights and practical advice for building effective NLP systems.

Overall, Foundations of Statistical Natural Language Processing is a must-read for anyone interested in the fascinating field of computational linguistics and NLP. Christopher Manning’s expertise and engaging writing style make this book an invaluable resource for understanding the foundations of statistical NLP.
#Foundations #Statistical #Natural #Language #Processing #Christopher #Manning

AI Ethics: A Textbook (Artificial Intelligence: Foundations, Theory, and – GOOD

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AI Ethics: A Textbook (Artificial Intelligence: Foundations, Theory, and – GOOD

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AI Ethics: A Textbook (Artificial Intelligence: Foundations, Theory, and Good Practices)

In the rapidly evolving field of artificial intelligence, ethics has become a topic of crucial importance. As AI technologies continue to advance and become more integrated into our daily lives, it is essential to consider the ethical implications of these powerful tools.

This textbook provides a comprehensive overview of the foundations, theory, and good practices related to AI ethics. It covers a wide range of topics, including bias and fairness in AI algorithms, privacy and data protection, accountability and transparency, and the societal impacts of AI.

Written by leading experts in the field, this textbook offers a balanced and insightful examination of the ethical challenges and opportunities presented by artificial intelligence. It provides readers with the knowledge and tools they need to navigate the complex ethical landscape of AI and make informed decisions about the development and deployment of these technologies.

Whether you are a student, researcher, policy maker, or industry professional, AI Ethics: A Textbook is a valuable resource for anyone interested in understanding and promoting ethical AI practices. Get your copy today and join the conversation on AI ethics.
#Ethics #Textbook #Artificial #Intelligence #Foundations #Theory #GOOD

Explainable AI: Foundations, Methodologies and Applications by Mayuri Mehta Pape

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Explainable AI: Foundations, Methodologies and Applications by Mayuri Mehta Pape

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Explainable AI: Foundations, Methodologies and Applications by Mayuri Mehta

In this groundbreaking book, author Mayuri Mehta delves into the world of Explainable Artificial Intelligence (AI) and explores its foundations, methodologies, and real-world applications. Mehta provides a comprehensive overview of the importance of explainability in AI systems, which is crucial for building trust, accountability, and transparency in these complex technologies.

The book covers a wide range of topics, including the history of AI explainability, the different methodologies and techniques used to make AI systems more interpretable, and the various applications of explainable AI in fields such as healthcare, finance, and autonomous vehicles. Mehta also discusses the challenges and limitations of explainable AI, as well as future research directions in this rapidly evolving field.

Whether you are a researcher, practitioner, or simply curious about the inner workings of AI systems, Explainable AI: Foundations, Methodologies and Applications is a must-read that will deepen your understanding of this important aspect of artificial intelligence. Don’t miss out on this essential resource for anyone interested in the future of AI.
#Explainable #Foundations #Methodologies #Applications #Mayuri #Mehta #Pape

Cloud Computing for Optimization: Foundations, Applications, and Challenges by B

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Cloud Computing for Optimization: Foundations, Applications, and Challenges by B

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Author B introduces a comprehensive guide on cloud computing for optimization in their latest book, “Cloud Computing for Optimization: Foundations, Applications, and Challenges.”

In this post, we will delve into the key insights and takeaways from the book, which covers the fundamental principles of cloud computing, its applications in optimization, and the challenges faced in implementing cloud-based optimization solutions.

Author B starts by providing a detailed overview of cloud computing and its various models, such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). They explain how cloud computing can enable organizations to optimize their resources, improve scalability, and reduce costs through on-demand access to computing resources.

The book also explores the applications of cloud computing in optimization, including cloud-based optimization algorithms, metaheuristics, and machine learning techniques. Author B highlights how cloud computing can facilitate the parallelization of optimization algorithms, leading to faster and more efficient solutions for complex optimization problems.

Furthermore, Author B discusses the challenges and considerations in implementing cloud-based optimization solutions, such as data security, privacy concerns, and interoperability issues. They provide strategies for overcoming these challenges and offer recommendations for designing and deploying cloud-based optimization systems effectively.

Overall, “Cloud Computing for Optimization: Foundations, Applications, and Challenges” offers a comprehensive and practical guide for researchers, practitioners, and students interested in leveraging cloud computing for optimization. It provides valuable insights into the potential of cloud computing to revolutionize the field of optimization and drive innovation in various industries.
#Cloud #Computing #Optimization #Foundations #Applications #Challenges, cloud computing

Unsupervised Learning: Foundations of Neural Computation by Geoffrey Hinton: New

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Unsupervised Learning: Foundations of Neural Computation by Geoffrey Hinton: New

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For all the data science enthusiasts out there, have you heard about the groundbreaking book “Unsupervised Learning: Foundations of Neural Computation” by Geoffrey Hinton? This book delves into the world of unsupervised learning, a crucial aspect of machine learning that focuses on finding patterns and relationships in data without the need for labeled examples.

Geoffrey Hinton, known as the “Godfather of Deep Learning,” provides a comprehensive overview of unsupervised learning techniques, including autoencoders, generative adversarial networks, and self-organizing maps. Through his expertise and insights, readers can gain a deeper understanding of how neural networks can learn from unlabeled data and extract meaningful representations.

Whether you’re a beginner looking to expand your knowledge or an experienced practitioner seeking to enhance your skills, “Unsupervised Learning: Foundations of Neural Computation” is a must-read. Stay ahead of the curve and unlock the potential of unsupervised learning with this invaluable resource.
#Unsupervised #Learning #Foundations #Neural #Computation #Geoffrey #Hinton