02790nam 2200589 a 450 991045174480332120200520144314.01-280-81942-197866108194230-8213-7004-9(CKB)1000000000473291(EBL)459457(OCoLC)144531228(SSID)ssj0000086189(PQKBManifestationID)12007262(PQKBTitleCode)TC0000086189(PQKBWorkID)10030071(PQKB)10992964(MiAaPQ)EBC459457(Au-PeEL)EBL459457(CaPaEBR)ebr10170134(CaONFJC)MIL81942(OCoLC)935270868(EXLCZ)99100000000047329120070523d2007 uf 0engur|n|---|||||txtccrA decade of action in transport[electronic resource] an evaluation of World Bank assistance to the transport sector, 1995-2005 /World Bank Independent Evaluation GroupWashington, D.C. World Bank20071 online resource (212 p.)Description based upon print version of record.0-8213-7003-0 Includes bibliographical references (p. 171-176).Contents; Abbreviations; Acknowledgments; Foreword; Executive Summary; Figures; Management Response to IEG Recommendations; Chairperson's Summary: Committee on Development Effectiveness (CODE); Statement of the External Advisory Panel; 1 Study Rationale, Objectives, and Organization; 2 Global Trends, Bank Strategy, and Sector Outcomes; 3 Bank Support to the Transport Sector; Tables; Boxes; 4 Promoting Private Sector Involvement; 5 Road Maintenance, Institutional Development, and Environmental Protection; 6 Transport and Poverty; 7 Internal Bank Performance Factors8 Findings, Lessons, and RecommendationsAppendixes; Endnotes; BibliographyThe World Bank committed 30.6 billion in transport-related projects during the past decade, making it one of the largest sectors. The evaluation looks into the Bank's experience in the sector, and assesses the institution's interventions, the impact of rapid transport sector expansion, and its readiness to meet the challenges ahead.TransportationDeveloping countriesEvaluationEconomic assistanceEvaluationElectronic books.TransportationEvaluation.Economic assistanceEvaluation.388/.0490971724MiAaPQMiAaPQMiAaPQBOOK9910451744803321A decade of action in transport2454970UNINA04521nam 22007335 450 991073483650332120240619102405.03-031-29642-710.1007/978-3-031-29642-0(CKB)27298744100041(MiAaPQ)EBC30620507(DE-He213)978-3-031-29642-0(PPN)272259241(MiAaPQ)EBC30612989(Au-PeEL)EBL30612989(EXLCZ)992729874410004120230629d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierNeural Networks and Deep Learning A Textbook /by Charu C. Aggarwal2nd ed. 2023.Cham :Springer International Publishing :Imprint: Springer,2023.1 online resource (xxiv, 529 pages) illustrations9783031296413 Includes bibliographical references and index.An Introduction to Neural Networks -- The Backpropagation Algorithm -- Machine Learning with Shallow Neural Networks -- Deep Learning: Principles and Training Algorithms -- Teaching a Deep Neural Network to Generalize -- Radial Basis Function Networks -- Restricted Boltzmann Machines -- Recurrent Neural Networks -- Convolutional Neural Networks -- Graph Neural Networks -- Deep Reinforcement Learning -- Advanced Topics in Deep Learning.This book covers both classical and modern models in deep learning. The chapters of this book span three categories: 1. The basics of neural networks: The backpropagation algorithm is discussed in Chapter 2. Many traditional machine learning models can be understood as special cases of neural networks. Chapter 3 explores the connections between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. 2. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 4 and 5. Chapters 6 and 7 present radial-basis function (RBF) networks and restricted Boltzmann machines. 3. Advanced topics in neural networks: Chapters 8, 9, and 10 discuss recurrent neural networks, convolutional neural networks, and graph neural networks. Several advanced topics like deep reinforcement learning, attention mechanisms, transformer networks, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 11 and 12. The book is written for graduate students, researchers, and practitioners. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques. The second edition is substantially reorganized and expanded with separate chapters on backpropagation and graph neural networks. Many chapters have been significantly revised over the first edition. Greater focus is placed on modern deep learning ideas such as attention mechanisms, transformers, and pre-trained language models.Machine learningData miningArtificial intelligenceExpert systems (Computer science)Natural language processing (Computer science)Machine LearningData Mining and Knowledge DiscoveryArtificial IntelligenceKnowledge Based SystemsNatural Language Processing (NLP)Xarxes neuronals (Informàtica)thubAprenentatge automàticthubLlibres electrònicsthubMachine learning.Data mining.Artificial intelligence.Expert systems (Computer science).Natural language processing (Computer science).Machine Learning.Data Mining and Knowledge Discovery.Artificial Intelligence.Knowledge Based Systems.Natural Language Processing (NLP).Xarxes neuronals (Informàtica)Aprenentatge automàtic006.32Aggarwal Charu C.518673MiAaPQMiAaPQMiAaPQBOOK9910734836503321Neural networks and deep learning1904942UNINA