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Hands-On Deep Learning with TensorFlow

You're reading from  Hands-On Deep Learning with TensorFlow

Product type Book
Published in Jul 2017
Publisher Packt
ISBN-13 9781787282773
Pages 174 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Dan Van Boxel Dan Van Boxel
Profile icon Dan Van Boxel
LinkedIn
Dan Van Boxel is a data scientist and machine learning engineer with over 10 years of experience. He is most well-known for Dan Does Data, a YouTube livestream demonstrating the power and pitfalls of neural networks. He has developed and applied novel statistical models of machine learning to topics such as accounting for truck traffic on highways, travel time outlier detection, and other areas. Dan has also published research articles and presented findings at the Transportation Research Board and other academic journals.
See other products by Dan Van Boxel

Table of Contents (12) Chapters

Hands-On Deep Learning with TensorFlow
Credits
About the Author
www.PacktPub.com
Customer Feedback
Preface
1. Getting Started 2. Deep Neural Networks 3. Convolutional Neural Networks 4. Introducing Recurrent Neural Networks 5. Wrapping Up Index

TensorFlow learn

Just as Scikit-Learn is a convenient interface to traditional machine learning algorithms, tf.contrib.learn (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/learn/python/learn), formerly known as skflow, it is a simplified interface to build and train DNNs. Now it comes free with every installation of TensorFlow!

Even if you're not a fan of the syntax, it's worth looking at TensorFlow Learn as the high-level API to TensorFlow. This is because it's currently the only officially supported one. But, you should know that there are many alternative high-level APIs that may have more intuitive interfaces. If interested, refer to Keras (https://keras.io/), tf.slim (included with TF), to learn more about TensorFlow-Slim refer to https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/slim or TFLearn (http://tflearn.org/).

Setup

To get started with TensorFlow Learn, you only need to import it. We'll also import the estimators function, which will...

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Authors (1)

Profile icon Dan Van Boxel
LinkedIn
Dan Van Boxel is a data scientist and machine learning engineer with over 10 years of experience. He is most well-known for Dan Does Data, a YouTube livestream demonstrating the power and pitfalls of neural networks. He has developed and applied novel statistical models of machine learning to topics such as accounting for truck traffic on highways, travel time outlier detection, and other areas. Dan has also published research articles and presented findings at the Transportation Research Board and other academic journals.
See other products by Dan Van Boxel

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