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

Product typeBook
Published inJul 2018
Reading LevelBeginner
PublisherPackt
ISBN-139781789538670
Edition1st Edition
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Author (1)
Will Ballard
Will Ballard
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Will Ballard

Will Ballard is the chief technology officer at GLG, responsible for engineering and IT. He was also responsible for the design and operation of large data centers that helped run site services for customers including Gannett, Hearst Magazines, NFL, NPR, The Washington Post, and Whole Foods. He has also held leadership roles in software development at NetSolve (now Cisco), NetSpend, and Works (now Bank of America). https://www.linkedin.com/in/will-ballard-b09115/
Read more about Will Ballard

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Summary

In this chapter, we learned about the MNIST digits, and how to acquire them; how tensors are really just multidimensional arrays; how we can encode image data as a tensor; how we can encode categorical or classification data as a tensor; and then we had a quick review and a cookbook approach to think about dimensions and tensors to get data prepared for machine learning.

Now that we've learned how to set up our input and output data for machine learning, we're going to move on to the next chapter, where we will create a Classical Neural Network (CNN).

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Hands-On Deep Learning for Images with TensorFlow
Published in: Jul 2018Publisher: PacktISBN-13: 9781789538670

Author (1)

author image
Will Ballard

Will Ballard is the chief technology officer at GLG, responsible for engineering and IT. He was also responsible for the design and operation of large data centers that helped run site services for customers including Gannett, Hearst Magazines, NFL, NPR, The Washington Post, and Whole Foods. He has also held leadership roles in software development at NetSolve (now Cisco), NetSpend, and Works (now Bank of America). https://www.linkedin.com/in/will-ballard-b09115/
Read more about Will Ballard