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Cognitive computing : theory and applications /
Cognitive Computing: Theory and Applications, written by internationally renowned experts, focuses on cognitive computing and its theory and applications, including the use of cognitive computing to manage renewable energy, the environment, and other scarce resources, machine learning models and alg...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam, Netherlands :
North-Holland,
2016.
|
| Colección: | Handbook of statistics (Amsterdam, Netherlands) ;
v. 35. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 0 | 0 | |a Cognitive computing : |b theory and applications / |c edited by Venkat N. Gudivada [and others]. |
| 264 | 1 | |a Amsterdam, Netherlands : |b North-Holland, |c 2016. | |
| 264 | 4 | |c �2016 | |
| 300 | |a 1 online resource (406 pages). | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Handbook of statistics | |
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Front Cover; Cognitive Computing: Theory and Applications; Copyright; Contents; Contributors; Preface; Audience; Organization; Section A: Fundamentals and Principles; Chapter 1: Cognitive Computing: Concepts, Architectures, Systems, and Applications; Chapter 2: Cognitive Computing and Neural Networks: Reverse Engineering the Brain; Section B: Complex Analytics and Machine Learning; Chapter 3: Visual Analytic Decision-Making Environments for Large-Scale Time-Evolving Graphs; Chapter 4: CyGraph: Graph-Based Analytics and Visualization for Cybersecurity. | |
| 505 | 8 | |a Chapter 5: Cognitive Analytics: Going Beyond Big Data Analytics and Machine LearningChapter 6: A Cognitive Random Forest: An Intra- and Intercognitive Computing for Big Data Classification Under Cune Condition; Chapter 7: Bayesian Additive Regression Tree for Seemingly Unrelated Regression with Automatic Tree Selection; Section C: Applications; Chapter 8: Cognitive Systems for the Food-Water-Energy Nexus; Chapter 9: Cognitive Computing Applications in Education and Learning; Chapter 10: Large-Scale Data Enabled Evolution of Spoken Language Research and Applications. | |
| 505 | 8 | |a Chapter 11: The Internet of Things and Cognitive ComputingSection A: Fundamentals and Principles; Chapter 1: Cognitive Computing: Concepts, Architectures, Systems, and Applications; 1. Introduction; 1.1. Chapter Organization; 2. Interdisciplinary Nature of Cognitive Science; 3. Cognitive Computing Systems; 4. Representations for Information and Knowledge; 5. Principal Technology Enablers of Cognitive Computing; 5.1. Big Data and Data Science; 5.2. Performance, Scalability, and Elasticity; 5.3. Distributed Computing Architectures; 5.4. Massive Parallel Processing Through MapReduce. | |
| 505 | 8 | |a 5.5. Cloud Computing5.6. AI and Machine Learning; 5.7. Neuromorphic Computing; 6. Cognitive Computing Architectures and Approaches; 6.1. Cognitivist Architectures and Approaches; 6.1.1. ACT-R; 6.1.2. Soar; 6.1.3. Mala; 6.1.4. GOMS; 6.1.5. Limitations; 6.2. Connectionist Architectures and Approaches; 6.2.1. ANN; 6.2.2. Lexical and Compositional Semantics; 6.2.3. NEF; 6.2.4. Deep Learning; 6.3. Hybrid Architectures and Approaches; 6.3.1. LIDA; 6.3.2. Sigma; 6.3.3. HTM; 6.3.4. IBM Watson; 6.3.5. Hierarchical Bayesian Model; 6.3.6. Textual Narrative to 3D Geometry Models. | |
| 505 | 8 | |a 7. Cognitive Computing Systems and Applications7.1. Intelligent Tutoring Systems; 7.2. Problem Solving Systems; 7.3. Question Answering; 7.4. Health Care; 7.5. Cognitive Businesses; 7.6. Human-Robot Interaction; 7.7. Cognitive Robots; 7.8. Deep Learning and Image Search; 7.9. Cross-media Retrieval; 7.10. Brain-Computer Interfaces; 7.11. Autonomous Vehicle Navigation; 8. Trends and Future Research Directions; 9. Cognitive Computing Resources; 9.1. Open Source Frameworks, Tools, and Digital Libraries; 9.2. Nonopen Source Infrastructures and Cognitive Computing Systems; References. | |
| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a Cognitive Computing: Theory and Applications, written by internationally renowned experts, focuses on cognitive computing and its theory and applications, including the use of cognitive computing to manage renewable energy, the environment, and other scarce resources, machine learning models and algorithms, biometrics, Kernel Based Models for transductive learning, neural networks, graph analytics in cyber security, neural networks, data driven speech recognition, and analytical platforms to study the brain-computer interface. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowned experts in their respective areas. | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 2 | |a Artificial Intelligence |0 (DNLM)D001185 | |
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| 700 | 1 | |a Gudivada, Venkat N., |e editor. | |
| 776 | 0 | 8 | |i Print version: |t Cognitive computing. |d Amsterdam, Netherlands : North-Holland, 2016 |z 0444637443 |z 9780444637444 |w (OCoLC)946605577 |
| 830 | 0 | |a Handbook of statistics (Amsterdam, Netherlands) ; |v v. 35. | |
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/handbooks/01697161/35 |z Texto completo |