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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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Bibliographic Details
Main Authors: Hope, Tom, Resheff, Yehezkel S. (Author), Lieder, Itay (Author)
Format: eBook
Language:English
Published: Sebastopol, CA O'Reilly Media 2017
Edition:First edition
Subjects:
Machine Learning / Http://id.loc.gov/authorities/subjects/sh85079324
Artificial Intelligence / Http://id.loc.gov/authorities/subjects/sh85008180
Machine Learning / Fast
Artificial Intelligence / Fast
Intelligence Artificielle
Artificial Intelligence / Aat
Tensorflow (electronic Resource)
Apprentissage Automatique
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Table of Contents:
  • 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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