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Machine Learning with TensorFlow 1.x

You're reading from   Machine Learning with TensorFlow 1.x Second generation machine learning with Google's brainchild - TensorFlow 1.x

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781786462961
Length 304 pages
Edition 1st Edition
Languages
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Authors (3):
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 Hua Hua
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Hua
 Ahmed Ahmed
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Ahmed
 Ul Azeem Ul Azeem
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Ul Azeem
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Toc

Table of Contents (19) Chapters Close

Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Getting Started with TensorFlow FREE CHAPTER 2. Your First Classifier 3. The TensorFlow Toolbox 4. Cats and Dogs 5. Sequence to Sequence Models-Parlez-vous Français? 6. Finding Meaning 7. Making Money with Machine Learning 8. The Doctor Will See You Now 9. Cruise Control - Automation 10. Go Live and Go Big 11. Going Further - 21 Problems 12. Advanced Installation

Taking it further


Suppose you just trained a nifty classifier showing some predictive power over the markets, should you start trading? Much like with the other machine learning projects we've done to date, you will need to test on an independent test set. In the past, we've often cordoned off our data into the following three sets:

  • The training set
  • The development set, aka the validation set
  • The test set

We can do something similar to our current work, but the financial markets give us an added resource—ongoing data streams!

We can use the same data source we used for our earlier pulls and continue to pull more data; essentially, we have an ever-expanding, unseen dataset! Of course, some of this depends on the frequency of the data that we use—if we operate on daily data, it will take a while to accomplish this. Operating on hourly or per-minute data makes this easier as we'll have more data quickly. Operating on tick-level data, based on the volume of quotes, is usually even better.

As real...

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