September 2019
Intermediate to advanced
420 pages
10h 29m
English
book
Machine Learning for OpenCV 4 - Second Edition
by Aditya Sharma, Michael Beyeler (USD), Vishwesh Ravi Shrimali, Michael Beyeler
Content preview from Machine Learning for OpenCV 4 - Second Edition
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What this book covers
Chapter 1, A Taste of Machine Learning, starts us off with installing the required software and Python modules for this book.
Chapter 2, Working with Data in OpenCV, takes a look at some basic OpenCV functions.
Chapter 3, First Steps in Supervised Learning, will cover the basics of supervised learning methods in machine learning. We will have a look at some examples of supervised learning methods using OpenCV and the scikit-learn library in Python.
Chapter 4, Representing Data and Engineering Features, will cover concepts such as feature detection and feature recognition using ORB in OpenCV. We will also try to understand important concepts such as the curse of dimensionality.
Chapter 5, Using Decision Trees to Make ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.