Mastering computer vision problems with state-of-the-art deep learning architectures, MXNet, and GPU virtual machines /

A presentation from the Strata Data 2017 London conference.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Formato: Electrónico Video
Idioma:Inglés
Publicado: [Place of publication not identified] : O'Reilly Media, [2017]
Temas:
Strata Data Conference > (2017 : > London, Great Britain)
Neural networks (Computer science)
Big data.
Ubiquitous computing.
Data mining.
Neural Networks, Computer
Data Mining
Réseaux neuronaux (Informatique)
Données volumineuses.
Informatique omniprésente.
Exploration de données (Informatique)
Electronic videos.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario:A presentation from the Strata Data 2017 London conference.
"Miguel González-Fierro explains how to train a state-of-the-art deep neural network, ResNet, using Microsoft RSever and MXNet with the ImageNet dataset. (While most of the deep learning libraries are programmed in C++ and Python, only MXNet offers an API for R programmers.) Miguel then demonstrates how to operationalize this training for real-world business problems related to image classification."--Resource description page.
Notas:Title from title screen (viewed July 12, 2018).
Descripción Física:1 online resource (1 streaming video file (38 min., 5 sec.))

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