Machine Learning for OpenCV - Advanced Methods and Deep Learning [Video]

Machine Learning for OpenCV - Advanced Methods and Deep Learning [Video]

Michael Beyeler

A practical introduction to the world of machine learning and image processing using OpenCV and Python
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Video Description

Computer vision is one of today's most exciting application fields of Machine Learning, From self-driving cars to medical diagnosis, computer vision has been widely used in various domains.

This course will cover essential concepts such as classifiers and clustering and will also help you get acquainted with neural networks and Deep Learning to address real-world problems.

All the code and supporting files for this course are available on Github at https://github.com/PacktPublishing/Machine-Learning-for-OpenCV-Advanced-Methods-and-Deep-Learning

The course will also guide you through creating custom graphs and visualizations, and show you how to go from raw data to beautiful visualizations. By the end of this course, you will be ready to create your own ML system and will also be able to take on your own machine learning problems.

Style and Approach

This course walks you through the key elements of OpenCV and its powerful Machine Learning classes while demonstrating how to get to grips with a range of models.

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What You Will Learn

  • Implement a Na├»ve Bayes classifier
  • Discover hidden structures in your data using k-means clustering
  • Implement k-means clustering and Expectation Maximization in OpenCV
  • Implement a simple multi-layer perceptron in OpenCV
  • Train and tweak neural networks
  • Build an ensemble classifier from decision trees in OpenCV
  • Combine different algorithms into a simple majority-vote classifier
  • Learn to tweak the hyperparameters of a model

Authors

Video Details

ISBN 139781789340525
Course Length2 hours 25 minutes
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