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Machine Learning Solutions

You're reading from   Machine Learning Solutions Expert techniques to tackle complex machine learning problems using Python

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788390040
Length 566 pages
Edition 1st Edition
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Author (1):
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Jalaj Thanaki Jalaj Thanaki
Author Profile Icon Jalaj Thanaki
Jalaj Thanaki
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Toc

Table of Contents (19) Chapters Close

Machine Learning Solutions
Foreword
Contributors
Preface
1. Credit Risk Modeling 2. Stock Market Price Prediction FREE CHAPTER 3. Customer Analytics 4. Recommendation Systems for E-Commerce 5. Sentiment Analysis 6. Job Recommendation Engine 7. Text Summarization 8. Developing Chatbots 9. Building a Real-Time Object Recognition App 10. Face Recognition and Face Emotion Recognition 11. Building Gaming Bot List of Cheat Sheets Strategy for Wining Hackathons Index

Testing the model


Now we need to load the trained model and test it. Here, we will be using the video stream. The FER application will detect the emotion based on my facial expression. You can refer to the code using this GitHub link: https://github.com/jalajthanaki/Facial_emotion_recognition_using_TensorFlow/blob/master/emotion_recognition.py.

You can find the code snippet for this in the following figure:

Figure 10.35: Code snippet for loading the trained model and performing testing

In order to start testing, we need to execute the following command:

$ python emotion_recognition.py poc

This testing will use your webcam. I have some demo files that I want to share here. Refer to the following figure:

Figure 10.36: Code snippet for FER application identifying the emotion of disgust

Also refer to the the following figure:

Figure 10.37: tThe FER application identifying the happy emotion

Refer to the code snippet in the following figure:

Figure 10.38: Code snippet for the FER application identifying...

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