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Machine Learning for OpenCV 4

You're reading from   Machine Learning for OpenCV 4 Intelligent algorithms for building image processing apps using OpenCV 4, Python, and scikit-learn

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Product type Paperback
Published in Sep 2019
Publisher Packt
ISBN-13 9781789536300
Length 420 pages
Edition 2nd Edition
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Authors (4):
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Aditya Sharma Aditya Sharma
Author Profile Icon Aditya Sharma
Aditya Sharma
Michael Beyeler (USD) Michael Beyeler (USD)
Author Profile Icon Michael Beyeler (USD)
Michael Beyeler (USD)
Vishwesh Ravi Shrimali Vishwesh Ravi Shrimali
Author Profile Icon Vishwesh Ravi Shrimali
Vishwesh Ravi Shrimali
Michael Beyeler Michael Beyeler
Author Profile Icon Michael Beyeler
Michael Beyeler
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Toc

Table of Contents (18) Chapters Close

Preface 1. Section 1: Fundamentals of Machine Learning and OpenCV FREE CHAPTER
2. A Taste of Machine Learning 3. Working with Data in OpenCV 4. First Steps in Supervised Learning 5. Representing Data and Engineering Features 6. Section 2: Operations with OpenCV
7. Using Decision Trees to Make a Medical Diagnosis 8. Detecting Pedestrians with Support Vector Machines 9. Implementing a Spam Filter with Bayesian Learning 10. Discovering Hidden Structures with Unsupervised Learning 11. Section 3: Advanced Machine Learning with OpenCV
12. Using Deep Learning to Classify Handwritten Digits 13. Ensemble Methods for Classification 14. Selecting the Right Model with Hyperparameter Tuning 15. Using OpenVINO with OpenCV 16. Conclusion 17. Other Books You May Enjoy

Summary

In this chapter, we briefly looked at the OpenVINO toolkit—what it is, what it's used for, and how we can install it. We also looked at how to run the demos and samples provided with the toolkit to understand and witness the power of OpenVINO. Finally, we saw how to harness this power in our pre-existing OpenCV codes by just adding one line specifying the backend to be used for model inference.

You might have also noticed that we didn't cover much hands-on content in this chapter. That's because OpenVINO is more suited for deep learning applications, which are not in the scope of this book. If you are a deep learning enthusiast, you should definitely go through the documentation provided by Intel on the OpenVINO toolkit and get started. It will definitely prove very useful to you.

In the next chapter, we will quickly go over a summary of all of the...

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