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Hands-On Machine Learning on Google Cloud Platform

You're reading from   Hands-On Machine Learning on Google Cloud Platform Implementing smart and efficient analytics using Cloud ML Engine

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788393485
Length 500 pages
Edition 1st Edition
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Authors (3):
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Alexis Perrier Alexis Perrier
Author Profile Icon Alexis Perrier
Alexis Perrier
V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Toc

Table of Contents (18) Chapters Close

Preface 1. Introducing the Google Cloud Platform 2. Google Compute Engine FREE CHAPTER 3. Google Cloud Storage 4. Querying Your Data with BigQuery 5. Transforming Your Data 6. Essential Machine Learning 7. Google Machine Learning APIs 8. Creating ML Applications with Firebase 9. Neural Networks with TensorFlow and Keras 10. Evaluating Results with TensorBoard 11. Optimizing the Model through Hyperparameter Tuning 12. Preventing Overfitting with Regularization 13. Beyond Feedforward Networks – CNN and RNN 14. Time Series with LSTMs 15. Reinforcement Learning 16. Generative Neural Networks 17. Chatbots

Vision API

The Vision API lets us build quite a few applications related to vision:

  • Detecting labels in an image
  • Detecting the text in an image
  • Face detection
  • Emotion detection
  • Logo detection
  • Landmark detection

Before we dive into building applications using the preceding, let's get a quick understanding of how they might be built, using face emotion detection as an example.

The process of detecting emotions involves:

  1. Collecting a huge set of images
  2. Hand-labeling images with the emotion that is likely represented in the image
  3. Training a convolutional neural network (CNN) (to be discussed in future chapters) to classify the emotion, based on an image as input

While the preceding steps are heavily resource intensive (as we would need a lot of humans to collect and hand-label images), there are multiple other ways to obtain face emotion detection. We are not sure how Google...

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