Learning TensorFlow : a guide to building deep learning systems /

Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks fo...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Hope, Tom (Data scientist) (Autor), Resheff, Yehezkel S. (Autor), Lieder, Itay (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Sebastopol, CA : O'Reilly Media, 2017.
Edición:First edition.
Temas:
TensorFlow (Electronic resource)
Machine learning.
Artificial intelligence.
Apprentissage automatique.
Intelligence artificielle.
artificial intelligence.
Artificial intelligence
Machine learning
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Introduction
  • Go with the flow : up and running with TensorFlow
  • Understanding TensorFlow basics
  • Convolution neural networks
  • Text I : working with text and sequences, and TensorBoard visualization
  • Text II : word vectors, advanced RNN, and embedding visualization
  • TensorFlow abstractions and simplifications
  • Queues, threads, and reading data
  • Distributed TensorFlow
  • Exporting and serving models with TensorFlow.

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