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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
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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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Predictions with TensorFlow

We will perform the hello world example of deep learning. This example is used to check and ensure that a model is working as intended. For this, we will use the MNIST dataset.

Introduction to the MNIST dataset

MNIST stands for Mixed National Institute of Standards and Technology, which has produced a handwritten digits dataset. This is one of the most researched datasets in machine learning, and is used to classify handwritten digits. This dataset is helpful for predictive analytics because of its sheer size, allowing deep learning to work its magic efficiently. This dataset contains 60,000 training images and 10,000 testing images, formatted as 28 x 28 pixel monochrome images. The following screenshot...

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