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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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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 baseline model


In this section, we will run the baseline model. In order to run the script, we need to jump to the location where we put the script titled real_time_object_detection.py and, on Command Prompt, we need to execute the following command:

Figure 9.13: Execution of the baseline approach

Take a look at the following figure. Here, I have just placed example images, but you can see the entire video when you run the script. Here is the link to see the entire video for real-time object detection using the baseline approach: https://drive.google.com/drive/folders/1RwKEUaxTExefdrSJSy44NugqGZaTN_BX?usp=sharing.

Figure 9.14: Output of the baseline approach (image is part of the video stream)

Here, the mAP for the MobileNet SSD is 71.1% . You will learn how to optimize this approach in the upcoming section. First, we will list down the points that we can improve in the next iteration. So, let's jump to our next section.

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