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Mastering Predictive Analytics with scikit-learn and TensorFlow

You're reading from   Mastering Predictive Analytics with scikit-learn and TensorFlow Implement machine learning techniques to build advanced predictive models using Python

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789617740
Length 154 pages
Edition 1st Edition
Languages
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Author (1):
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Alvaro Fuentes Alvaro Fuentes
Author Profile Icon Alvaro Fuentes
Alvaro Fuentes
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Predictive Analytics with TensorFlow and Deep Neural Networks

TensorFlow is an open source library developed by Google Brain Team. It is used in large-scale machine learning applications, such as neural networks, and for making numerical computations. Developers are able to create dataflow graphs using TensorFlow. These graphs show the movement of data. TensorFlow can be used to train and run deep neural networks for various applications such as image recognition, machine language translation, and natural language processing.

We already know that predictive analytics is about providing predictions about unknown events. We are going to use it here with TensorFlow.

In this chapter, we will cover the following topics:

  • Predictions with TensorFlow
  • Regression with Deep Neural networks (DNNs)
  • Classification with DNNs
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