1.065 hasil untuk machine learning
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Clinical Implementation of AI-Driven Neurological Triage: Workflow Integration, Validation Frameworks and Outcome Optimization
…and epilepsy. Through evidence-based frameworks, the book explains how machine learning algorithms and predictive analytics can prioritize patient risk, optimize imaging interpretation, and support clinician decision pathways. It also discusses ethical and regulatory aspects, validation protocols…
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Macrophage Heterogeneity and Immune Checkpoints in Atherosclerosis: SingleCell Transcriptomics and Artificial Intelligence-Driven Insights
…of inflammatory imbalance within arterial plaques. It highlights how machine-learning models refine cell-state classification, predict functional transitions, and reveal regulatory networks that remain hidden in conventional analyses. With a focus on translational relevance, the book demonstrates…
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Decolonizing Artificial Intelligence: From Colonial Inheritance to Pluriversal Reconstruction Independent Dissertation, Volume II Version 2.1
…intelligence through data selection, training objectives, reinforcement learning, alignment systems, and corporate governance. It establishes the necessity of decolonizing AI at inception rather than attempting to correct discriminatory and extractive outcomes after deployment. Building upon the…
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Business Analytics
…contemporary developments shaping the future of analytics, including machine learning, artificial intelligence, deep learning, the Internet of Things (IoT), and robotics. Each chapter is reinforced with case studies, multiple-choice questions, and review questions to facilitate learning and…
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Mostafa El-Rakhawi Doctrine in Cybernetic Law: Feedback Loops and Self-Evolving Legislation as a Framework for Adaptive Governance and Judicial Excellence
…components. The doctrine applies control theory, information theory, and machine learning to judicial practice, providing practical templates, checklists, and Python implementations. It covers 12 jurisdictions (Egypt, Algeria, France, Germany, UK, USA, Japan, Australia, India, Brazil, South Africa…
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Proceedings of the 7th Summer School on Cyber-Physical Systems and Internet-of-Things Including AIoT Academy 2026
…From Energy-Efficient and Secure AI to Emerging Trends in Quantum Machine Learning: Challenges, Methods, Applications, and Systems .................................... 93 Abdelhakim Baouya, Brahim Hamid, Otmane Ait Mohamed and Saddek Bensalem Secure and Resilient Engineering of Cyber-Physical…
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Engineering Intelligent AIOT Systems-Artificial Intelligence for Smart Connected Technologies BY Dr. Srinivas Kumar Palvadi, Dr. Babu Rajendra Prasad Singothu, Kondapalli Krupa Sagari, Mr. Nyakapu Rajender
…systems. It explains sensor data acquisition, feature engineering, machine learning, deep learning, computer vision, natural language processing, reinforcement learning, explainable AI, federated learning, and privacy-preserving intelligence. The chapter concludes with a real-world AIoT healthcare…
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Quantum Intelligence: The Convergence of AI and Quantum Computing
…the fundamentals of quantum mechanics, quantum algorithms, and quantum machine learning, highlighting how quantum computing can accelerate data processing, optimization, pattern recognition, and complex decision-making. It covers key topics such as quantum neural networks, quantum-enhanced…
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The El-Rakhawi Creed The Practical and Scientific Guide for Judges, Lawyers, and Public Prosecution in Criminal Law and Forensic Medicine
…bridging biological pathology, legal evidentiary standards, and machine learning architectures. Authored by Dr. Mohamed Kamal Arafa Elrakhawi, this 29-chapter masterwork introduces revolutionary frameworks: the Algorithmic Daubert Framework for AI evidence admissibility, the Active Challenge…
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Artificial Intelligence and Emerging Technologies: Bridging Management Strategy and Engineering Innovation
…and society. The book examines how organizations can leverage AI, machine learning, data analytics, the Internet of Things (IoT), blockchain, automation, and digital transformation to enhance decision-making, operational efficiency, and innovation. By integrating perspectives from management and…
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AI & Python Programming for Pharmacy – B. Pharm Semester 1 (As Per NEP 2020)
…skills from the first semester. Key topics include AI fundamentals, machine learning, Python basics, and data handling, all contextualized for pharmaceutical applications. We hope this book serves as a valuable academic resource and inspires learners to explore the intersection of technology and…
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Physics-Informed AI for Defect Prediction in WAAM for Space Systems (Academic Edition)
…physics of WAAM, defect formation mechanisms, computational modeling, machine learning, physics-informed neural networks, and hybrid predictive architectures. Particular attention is given to challenges associated with data scarcity, process uncertainty, microgravity, and autonomous manufacturing…
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Medallion Architecture with Databricks
…cloud technologies while covering data governance, security, and machine learning integration within the Databricks ecosystem. Real-world case studies and best practices provide actionable knowledge for tackling complex data challenges. With its focus on scalability and performance, this book is a…
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Úvod do zpracování dat 1
This book sheds light on the various tools and methods used in data processing. Starting with proccessing numerical tables, the book moves on to image and text processing using machine learning, artificial neural networks and artificial intelligence. The driving idea behind this book is to convey…
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Artificial Intelligence: Exploring the Frontiers of Technology
…guides readers through the complex interactions between neural networks, machine learning, and algorithms, explaining how these technologies spur innovation in a variety of sectors. The book explores the effects of AI on society, the economy, and ethics, ranging from driverless cars to medical…
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Role of Artificial Intelligence in Rare Disease Diagnosis and Orphan Drug Discovery
…genomic sequencing, proteomic profiles, and clinical phenotypes. Machine learning and deep learning models can detect hidden associations among these heterogeneous data types, enabling earlier and more accurate identification of rare disorders. Natural language processing further enhances…
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ResNet Architectures and Applications: A Practical Guide From Theoretical Optimization Frameworks to Production PyTorch Architectures
…ceiling associated with ultra-deep networks, contemporary deep learning engineering has evolved the residual block far beyond its original 2016 baseline. Today, residual paradigms dictate the structural boundaries and optimization stability of state-of-the-art architectures across complex computer…
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Artificial Intelligence BY Dr.Shabana S.Pathan,Dr.Priti S. Uparkar
…with implementations, case studies, and emerging trends such as machine learning, deep learning, natural language processing, and ethical considerations in AI. This volume is designed primarily for undergraduate and postgraduate students, researchers, and industry practitioners seeking to build or…
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Data Science Beyond Boundaries: Architectures, Intelligence, and Scale by Dr. P. V. Naresh,Dr.K.M.Rayudu,Likitha Gongalla, R.Annapurna,Dr. Thota Siva Ratna Sai
…data science now integrates advanced architectures, scalable systems, machine intelligence, and interdisciplinary methodologies to address complex real-world challenges. This book, Data Science Beyond Boundaries: Architectures, Intelligence, and Scale , has been conceived to explore these emerging…
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ARTIFICIAL INTELLIGENCE BY Dr. Laxmi Choudhary,Mrs. Bhanupriya Sharma,Mr. Avinash Bhandiya,Dr. Satya Narayan
…a powerful collection of theories, algorithms, and systems capable of learning, reasoning, perception, and decision-making at unprecedented scales. The book Artificial Intelligence has been conceived with the objective of providing a comprehensive, structured, and contemporary understanding of AI…
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