Machine Learning for OpenCV 4
Machine Learning for OpenCV 4, Second Edition will help the readers to implement and train machine learning algorithms with OpenCV 4 and scikit-learn in Python. By the end of this book, you will be able to build intelligent applications with OpenCV 4 using various optimization techniques for your machine learning algorithms.
Offered by
Difficulty Level
Intermediate
Completion Time
14h
Language
English
About Book
Who Is This Book For?
This book is for Computer Vision professionals, machine learning developers, or anyone who wants to learn machine learning algorithms and implement them using OpenCV 4. If you want to build real-world Computer Vision and image processing applications powered by machine learning, then this book is for you. Working knowledge of Python programming is required to get the most out of this book.
Machine Learning for OpenCV 4
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 14h total length
A Taste of Machine Learning
Working with Data in OpenCV
First Steps in Supervised Learning
Representing Data and Engineering Features
Using Decision Trees to Make a Medical Diagnosis
Detecting Pedestrians with Support Vector Machines
Implementing a Spam Filter with Bayesian Learning
Discovering Hidden Structures with Unsupervised Learning
Using Deep Learning to Classify Handwritten Digits
Ensemble Methods for Classification
Selecting the Right Model with Hyperparameter Tuning
Using OpenVINO with OpenCV
Conclusion
Related Resources
Access Ready-to-Use Books for Free!
Get instant access to a library of pre-built books—free trial, no credit card required. Start training your team in minutes!