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Browsing Học liệu điện tử (Electronic learning materials) by Subject "Artificial intelligence"

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Now showing 1 - 5 of 5
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    AI and Blockchain Technology in 6G Wireless Network
    (Springer, 2022) Borah, Malaya Dutta; Singh, Pushpa; Deka, Ganesh Chandra
    This book highlights future research directions and latent solutions by integrating AI and Blockchain 6G networks, comprising computation efficiency, algorithms robustness, hardware development and energy management. This book brings together leading researchers in Academia and industry from diverse backgrounds to deliver to the technical community an outline of emerging technologies, advanced architectures, challenges, open issues and future directions of 6G networks. This book is written for researchers, professionals and students to learn about the integration of technologies such as AI and Blockchain into 6G network and communications. This book addresses the topics such as consensus protocol, architecture, intelligent dynamic resource management, security and privacy in 6G to integrate AI and Blockchain and new real-time application with further research opportunities.
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    Deep Learning-Powered Technologies : Autonomous Driving, Artificial Intelligence of Things (AIoT), Augmented Reality, 5G Communications and Beyond
    (Springer, 2023) Mohamed, Khaled Salah
    This book covers various, leading-edge deep learning technologies. The author discusses new applications of deep learning and gives insight into the integration of deep learning with various application domains, such as autonomous driving, augmented reality, AIOT, 5G and beyond.
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    Essentials of Python for Artificial Intelligence and Machine Learning
    (Springer, 2024) Gupta, Pramod; Bagchi, Anupam
    This book introduces the essentials of Python for the emerging fields of Machine Learning (ML) and Artificial Intelligence (AI). The authors explore the use of Python's advanced module features and apply them in probability, statistical testing, signal processing, financial forecasting, and various other applications. This includes mathematical operations with array data structures, Data Manipulation, Data Cleaning, machine learning, Data pipeline, probability density functions, interpolation, visualization, and other high-performance benefits using the core scientific packages NumPy, Pandas, SciPy, Sklearn/Scikit learn and Matplotlib. Readers will gain a deep understanding with problem-solving experience on these powerful platforms when dealing with engineering and scientific problems related to Machine Learning and Artificial Intelligence.
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    Limits of AI - Theoretical, Practical, Ethical
    (Springer, 2024) Mainzer, Klaus; Kahle, Reinhard
    Artificial intelligence is a key technology with great expectations in science, industry, and everyday life. This book discusses both the perspectives and the limitations of this technology. This concerns the practical, theoretical, and conceptual challenges that AI has to face. In an early phase of symbolic AI, AI focused on formal programs (e.g., expert systems), in which rule-based knowledge was processed with the help of symbolic logic. Today, AI is dominated by statistics-based machine learning methods and Big Data. While this sub-symbolic AI is extremely successful (e.g., chatbots like ChatGPT), it is often not transparent. The book argues for explainable and reliable AI, in which the logical and mathematical foundations of AI-algorithms become understandable and verifiable.
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    Machine Learning Empowered Intelligent Data Center Networking : Evolution, Challenges and Opportunities
    (Springer, 2023) Ting, Wang; Bo, Li; Mingsong, Chen; Shui, Yu
    An Introduction to the Machine Learning Empowered Intelligent Data Center Networking Fundamentals of Machine Learning in Data Center Networks. This book reviews the common learning paradigms that are widely used in data centernetworks, and offers an introduction to data collection and data processing in data centers. Additionally, it proposes a multi-dimensional and multi-perspective solution quality assessment system called REBEL-3S. The book offers readers a solid foundation for conducting research in the field of AI-assisted data center networks. Comprehensive Survey of AI-assisted Intelligent Data Center Networks. This book comprehensively investigates the peer-reviewed literature published in recent years. The wide range of machine learning techniques is fully reflected to allow fair comparisons.