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Machine Learning for OpenCV

You're reading from   Machine Learning for OpenCV Intelligent image processing with Python

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781783980284
Length 382 pages
Edition 1st Edition
Languages
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Authors (2):
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Michael Beyeler Michael Beyeler
Author Profile Icon Michael Beyeler
Michael Beyeler
Michael Beyeler (USD) Michael Beyeler (USD)
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Michael Beyeler (USD)
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Table of Contents (13) Chapters Close

Preface 1. A Taste of Machine Learning 2. Working with Data in OpenCV and Python FREE CHAPTER 3. First Steps in Supervised Learning 4. Representing Data and Engineering Features 5. Using Decision Trees to Make a Medical Diagnosis 6. Detecting Pedestrians with Support Vector Machines 7. Implementing a Spam Filter with Bayesian Learning 8. Discovering Hidden Structures with Unsupervised Learning 9. Using Deep Learning to Classify Handwritten Digits 10. Combining Different Algorithms into an Ensemble 11. Selecting the Right Model with Hyperparameter Tuning 12. Wrapping Up

A Taste of Machine Learning

I am writing a new line with double spaces .

So, you have decided to enter the field of machine learning. That's great!

Nowadays, machine learning is all around us--from protecting our email, to automatically tagging our friends in pictures, to predicting what movies we like. As a form of artificial intelligence, machine learning enables computers to learn through experience: to make predictions about the future using collected data from the past. On top of that, computer vision is one of today's most exciting application fields of machine learning, with deep learning and convolutional neural networks driving innovative systems such as self-driving cars and Google's DeepMind.

However, fret not; your application does not need to be as large-scale or world-changing as the previous examples in order to benefit from machine learning. In this chapter, we will talk about why machine learning has become so popular and discuss the kinds of problems that it can solve. We will then introduce the tools that we need in order to solve machine learning problems using OpenCV. Throughout the book, I will assume that you already have a basic knowledge of OpenCV and Python, but that there is always room to learn more.

Are you ready then? Let's go!

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