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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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Saif Ahmed Saif Ahmed
Author Profile Icon Saif Ahmed
Saif Ahmed
Quan Hua Quan Hua
Author Profile Icon Quan Hua
Quan Hua
Shams Ul Azeem Shams Ul Azeem
Author Profile Icon Shams Ul Azeem
Shams Ul Azeem
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with TensorFlow 2. Your First Classifier FREE CHAPTER 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

Setting up the project

In this chapter, we will fine-tune a VGG model that has been trained on ImageNet data with 1,000 classes. We have provided an initial project with a pretrained VGG model and some utility files. You can go ahead and download the code from https://github.com/mlwithtf/mlwithtf/tree/master/chapter_09.

In the folder chapter-09, you will have the following structure:

- data
--VGG16.npz
- samples_data
- production
- utils
--__init__.py
--debug_print.py
- README.md

There are two files that you should understand:

  • VGG16.npz is the pre-trained model that is exported from the Caffe model. Chapter 11, Going Further - 21 Problems will show you how to create this file from the Caffe model. In this chapter, we will use this as the initial values for our model. You can download this file from the README.md in the chapter_09 folder.
  • production is the Flask server that we...
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