{"title":"River Publishers Series In Rapids In Computing And Information Science And Technology","description":"\u003cp\u003eDelve into the world of cutting-edge computing with the River Publishers Series. Discover innovative research and technological advancements shaping the future of information science and technology.\u003c\/p\u003e","products":[{"product_id":"introduction-to-quantum-computing-book-ahmed-banafa-9788770228411","title":"Introduction to Quantum Computing","description":"This book explores quantum computing as a transformative technology and its applications in cryptography, teleportation, IoT, AI, Blockchain, and the futurist concept of quantum internet. It explains the fundamentals of quantum computing and how it’s different from classic computing. The challenges facing quantum computing will be discussed, and the types of quantum computing will be introduced and explained. 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They will also be introduced to the basic components of Blockchain (transaction, block, block header, and the chain), its operations (hashing, verification, validation, and consensus model), underlying algorithms, and essentials of trust (hard fork and soft fork). Private and public Blockchain networks similar to Bitcoin and Ethereum will be introduced, as will concepts of Smart Contracts, Proof of Work and Proof of Stack.  Blockchain is an emerging technology that can radically improve transaction security at banking, supply chain, and other transaction networks. It’s estimated that Blockchain will generate $3.1 trillion in new business value by 2030. 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Additionally, the book covers recurrent neural networks (RNNs) and their variants like long short-term memory (LSTM) and gated recurrent units (GRUs), which are crucial for time-series analysis and sequential data applications.  Supervised machine learning algorithms are meticulously explained, with practical examples to illustrate their application. The book covers logistic regression and its use in predicting sports outcomes, decision trees for plant classification, random forests for traffic prediction, and support vector machines for house price prediction. Gradient boosting machines and their applications in genomics, AdaBoost for bioinformatics data classification, and extreme gradient boosting (XGBoost) for churn prediction are also discussed, providing readers with a robust toolkit for various predictive tasks.  Unsupervised learning algorithms are another significant focus of the book, introducing readers to techniques for uncovering hidden patterns in data. Hierarchical clustering for gene expression data analysis, principal component analysis (PCA) for climate predictions, and singular value decomposition (SVD) for signal denoising are thoroughly explained. The book also explores applications like robot navigation and network security, demonstrating the versatility of these techniques.  Natural language processing (NLP) is comprehensively covered, highlighting its fundamental concepts and various applications. The book discusses the overview of NLP, its fundamental concepts, and its diverse applications such as chatbots, virtual assistants, clinical NLP applications, and social media analytics. Detailed sections on text pre-processing, syntactic analysis, machine translation, text classification, named entity recognition, and sentiment analysis equip readers with the knowledge to build sophisticated NLP models.  The final chapters of the book explore generative AI, including generative adversarial networks (GANs) for image generation, variational autoencoders for vibrational encoder training, and autoregressive models for time series forecasting. It also delves into Markov chain models for text generation, Boltzmann machines for pattern recognition, and deep belief networks for financial forecasting. 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Practical case studies and real-world examples are included to illustrate how NLP is applied in various sectors, including healthcare, finance, and customer service.  This book is an invaluable resource for students, researchers, and industry professionals seeking to understand the foundational concepts, cutting-edge advancements, and broader implications of NLP, equipping them with the knowledge to innovate and apply these technologies effectively in their respective fields.","brand":"WoB","offers":[{"title":"- \/ - \/ -","offer_id":51629200113937,"sku":"","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ GARDNERS","offer_id":51629200670993,"sku":"NGR9788770048293","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52653793247505,"sku":"NLS9788770048293","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/8770048290.jpg?v=1751097460"},{"product_id":"ai-in-education-systems-successful-cases-and-perspectives-book-vadym-i-slyusar-9788743809241","title":"AI in Education Systems: Successful Cases and Perspectives","description":"This River Rapid provides a timely analysis of the state of the art and future perspectives of artificial intelligence (AI) in education. Drawing on international expertise and successful case studies, it explores both the opportunities AI creates for teaching and learning and the challenges posed by its uncontrolled use by students and schoolchildren.  The book is structured into seven research-analytic chapters authored by leading scholars from Norway, Poland, Ukraine, and the United States. Together, they present a comprehensive picture of AI’s growing role in educational systems worldwide. Topics include:    An overview and comparative review of large language models. Analysis of successful AI applications in education based on global best practices. Strategies for bilingual education supported by AI tools. Risks of unsupervised AI use by pupils and students, both in education and on social media. The relationship between machine learning and human learning, with attention to pedagogical advances inspired by AI. Future directions for AI in enhancing teaching and learning processes. 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