Machine Learning with Tensorflow: A Deeper Look at Machine Learning with TensorFlow - E-book - ePub

Edition en anglais

Note moyenne 
 Frank Millstein - Machine Learning with Tensorflow: A Deeper Look at Machine Learning with TensorFlow.
TensorFlow is a powerful open source software library for performing various numerical data flow graphs. With its powerful resources, TensorFlow is perfect... Lire la suite
3,99 € E-book - ePub
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Résumé

TensorFlow is a powerful open source software library for performing various numerical data flow graphs. With its powerful resources, TensorFlow is perfect for machine learning enthusiasts offering plenty of workspace where you can improve your machine learning techniques and build your own machine learning algorithms. Thanks to its capability, in recent times TensorFlow definitely has made its way into the software mainstream, so everyone who is interested in machine learnings definitely should considers getting hands on TensorFlow practices.
With this book as your guide, you will get your hands on TensorFlow machine learning techniques, learn how to perform different neural network operations, learn how to deal with massive datasets and finally build your first machine learning model for data classification. Here Is a Preview of What You'll Learn Here. What is machine learning Main uses and benefits of machine learning How to get started with TensorFlow, installing and loading data Data flow graphs and basic TensorFlow expressions How to define your data flow graphs and how to use TensorBoard for data visualization Main TensorFlow operations and building tensors How to perform data transformation using different techniques How to build high performance data pipelines using TensorFlow Dataset framework How to create TensorFlow iterators Creating MNIST classifiers with one-hot transformation Get this book NOW and learn how to do various machine learning tasks using TensorFlow!

Caractéristiques

  • Date de parution
    20/10/2019
  • Editeur
  • ISBN
    978-1-386-68222-6
  • EAN
    9781386682226
  • Format
    ePub
  • Caractéristiques du format ePub
    • Protection num.
      pas de protection

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