“…With a foot in each camp, Silicon Valley VC and Stanford Graduate School of Business lecturer Robert Siegel demonstrates how to analyze and combine the best of both digital attributes and physical attributes to grow your company in the coming decade. …”

“…He credits the Pill with radically altering his academic career at Stanford University to become one of the few American chemists writing novels and plays." …”

Tabla de Contenidos:

Tabla de Contenidos: “…. -- Classifying data points using the Stanford classifier -- Getting ready -- How to do it... -- How it works... -- Classifying data points using Massive Online Analysis (MOA)…”

“…The symposium was organized by the University of Cyprus together with the Center for Turbulence Research at Stanford University and NASA Ames Research Center. …”

“…Jones traces Rubbo’s filmmaking from his days as a film student at Stanford, through his twenty years at the National Film Board of Canada, where Rubbo developed his distinct documentary style. …”

“…—JEFFREY PFEFFER, Ph.D., professor, Stanford Graduate School of Business, and author of Power: Why Some People Have It—and Others Don’t “Your ability to influence and persuade others is the single most important skill for success in business and leadership—and this book shows you how with simple, powerful, practical, and proven techniques.” …”

“…Der inzwischen leider verstorbene Hans Lemberg zeichnete damals den wissenschaftlichen Lebensweg des Jubilars in bewegender Weise nach, von den Archivstudien des jungen Doktoranden in der Tschechoslowakei der 1960er Jahre über die Tätigkeit am Collegium Carolinum in München, an der Freien Universität Berlin und die internationalen Wanderjahre, die ihn nach Florenz, New York, Stanford und Sapporo geführt hatten, bis er nach einem kurzen Intermezzo in Oldenburg 1991 auf die Stiftungsprofessur für "Kultur und Geschichte der Deutschen im östlichen Europa" an die Heinrich-Heine-Universität in Düsseldorf berufen wurde…”

“…Volume 28, including contributions from Stanford University and Harvard Business School, examines topics such as: graded status characteristics and expectation states; standardizing open interaction coding for status processes; creating community through language among San Pedro Longshoremen; applying identity theory to moral acts of commission and omission; and joint commitments and social groups. …”

“…Scott Hartley escuchó por primera vez los términos difuso y técnico mientras estudiaba ciencias políticas en la Universidad de Stanford. Si te especializaste en humanidades o ciencias sociales, eras un borroso. …”

Tabla de Contenidos: “…, 2.3 Variations on the Basic Learning Curve Models, 2.3.1 DeJong Unit Learning Curve, 2.3.2 DeJong-Wright Cumulative Average Hybrid Learning Curve, 2.3.3 Stanford-B Unit Learning Curve, 2.3.4 Stanford-Wright Cumulative Average Hybrid Learning Curve, 2.3.5 S-Curve Unit Learning Curve, 2.3.6 S-Curve-Wright Cumulative Average Hybrid Learning Curve, 2.4 Where and When to Apply Learning and How Much?…”

“…Pardos, Mulattos, and the Quest for Social Mobility in the Spanish Indies, Stanford: Stanford University Press, 2015."Un trabajo enorme y potente, tanto en términos de extensión como de profundidad y de erudición. …”

Tabla de Contenidos: “…8.3 Características de los grupos efectivos8.4 El modelo de Gene Stanford; 8.5 Etapas de desarrollo de un grupo; 9. …”

Tabla de Contenidos: “…Test de Cociente Intelectual de Stanford-Binet; 3.1.3. Escala de Merril Palmer; 3.2. …”

Tabla de Contenidos: “…Chapter 5: Unsupervised Learning - Clustering and Dimensionality Reduction -- Dimensionality reduction -- Unsupervised dimensionality reduction -- Principal Component Analysis -- Truncated SVD -- Truncated SVD for categorical and sparse data -- Random projection -- Cluster analysis -- Hierarchical methods -- K-means -- Choosing K in K-Means -- DBSCAN -- Clustering for supervised learning -- Clusters as features -- Clustering as dimensionality reduction -- Supervised learning via clustering -- Evaluation -- Manual evaluation -- Supervised evaluation -- Unsupervised Evaluation -- Summary -- Chapter 6: Working with Text - Natural Language Processing and Information Retrieval -- Natural Language Processing and information retrieval -- Vector Space Model - Bag of Words and TF-IDF -- Vector space model implementation -- Indexing and Apache Lucene -- Natural Language Processing tools -- Stanford CoreNLP -- Customizing Apache Lucene -- Machine learning for texts -- Unsupervised learning for texts -- Latent Semantic Analysis -- Text clustering -- Word embeddings -- Supervised learning for texts -- Text classification -- Learning to rank for information retrieval -- Reranking with Lucene -- Summary -- Chapter 7: Extreme Gradient Boosting -- Gradient Boosting Machines and XGBoost -- Installing XGBoost -- XGBoost in practice -- XGBoost for classification -- Parameter tuning -- Text features -- Feature importance -- XGBoost for regression -- XGBoost for learning to rank -- Summary -- Chapter 8: Deep Learning with DeepLearning4J -- Neural Networks and DeepLearning4J -- ND4J - N-dimensional arrays for Java -- Neural networks in DeepLearning4J -- Convolutional Neural Networks -- Deep learning for cats versus dogs -- Reading the data -- Creating the model -- Monitoring the performance -- Data augmentation -- Running DeepLearning4J on GPU -- Summary…”

Tabla de Contenidos: “…Machine generated contents note: Foreword Ulf Ewaldsson, VP, Ericsson Foreword Lauri Oksanen, VP, Nokia Networks Part 1 : Introduction 1 Overview Madhusanka Liyanage, Mika Ylianttila, Andrei Gurtov 1.1 Present Mobile networks and its Limitations 1.2 Software Defined Mobile Network 1.3 Key Benefits of SDMN 1.4 Conclusion 2 Mobile Network History Brian Brown, Rob Gonzalez, Brian Stanford 2.1 Chapter Overview 2.2 The Evolution of the Mobile Network 2.3 Limitations and Challenges in Current Mobile Networks 2.4 Requirement in future mobile networks 3 Software Defined Networking Concepts Xenofon Foukas, Mahesh K -- Marina, Kimon Kontovasilis 3.1 Introduction 3.2 SDN History and Evolution 3.3 SDN Paradigm and Applications 3.4 Impact of SDN to Research and Industry 4 Wireless Software Defined Networking Claude Chaudet, Yoram Haddad 4.1 Introduction 4.2 SDN for wireless 4.3 Related Works 4.4 Wireless SDN opportunities 4.5 Wireless SDN challenges 4.6 Conclusion 5 Leveraging SDN for The 5G Networks: Trends, Prospects and Challenges Akram Hakiri, Pascal Berthou 5.1 Introduction 5.2 Evolution of the Wireless Communication towards the 5G 5.3 Software-Defined Networks 5.4 Network Function Virtualization 5.5 Information-Centric Networking 5.6 Mobile and Wireless Networks 5.7 Cooperative Cellular Networks 5.8 Unification of the control plane 5.9 Supporting automatic QoS provisioning 5.10 Cognitive Network Management and Operation 5.11 Role of Satellites in the 5G networks 5.12 Conclusion Part II : SDMN Architectures and Network implementation 6 LTE architecture integration with SDN Jose Costa-Requena, Raimo Kantola, Jesús Llorente Santos, Vicent Ferrer Guasch, Maël Kimmerlin, Antti Mikola, Jukka Manner 6.1 Chapter Overview 6.2 Restructuring mobile networks to SDN 6.3 Mobile Backhaul Scaling 6.4 Security and distributed FW 6.5 SDN and LTE integration benefits 6.6 SDN and LTE integration benefits for end users 6.7 Related work and Research questions 6.8 Conclusions 7 EPC in the Cloud James Kempf, Kumar Balachandran 7.1 Introduction 7.1.3 SDN and Cross-domain Service Development 7.2 EPC in the Cloud Version 1.0 7.3 EPC in the Cloud Version 2.0? …”