Scaling up machine learning : parallel and distributed approaches /

This integrated collection covers a range of parallelization platforms, concurrent programming frameworks and machine learning settings, with case studies.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Bekkerman, Ron (Editor ), Bilenko, Mikhail, 1978- (Editor ), Langford, John, 1975- (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York : Cambridge University Press, [2012]
Temas:
Machine learning.
Data mining.
Parallel algorithms.
Parallel programs (Computer programs)
Data Mining
Apprentissage automatique.
Exploration de données (Informatique)
Algorithmes parallèles.
Programmes parallèles (Logiciels)
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Cover; Scaling Up Machine Learning; Title; Copyright; Contents; Contributors; Preface; CHAPTER 1 Scaling Up Machine Learning: Introduction; 1.1 Machine Learning Basics; 1.2 Reasons for Scaling Up Machine Learning; 1.2.1 Large Number of Data Instances; 1.2.2 High Input Dimensionality; 1.2.3 Model and Algorithm Complexity; 1.2.4 Inference Time Constraints; 1.2.5 Prediction Cascades; 1.2.6 Model Selection and Parameter Sweeps; 1.3 Key Concepts in Parallel and Distributed Computing; 1.3.1 Data Parallelism; 1.3.2 Task Parallelism; 1.4 Platform Choices and Trade-Offs; 1.5 Thinking about Performance.

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