Machine Learning for OpenCV: Intelligent image processing with Python

Great explanation of the fundamentals of machine learning. It's much broader than just machine learning for computer vision but does narrow to computer vision. The source code printed in the book seems like some early in development version - there are many broken code sections but the code is fixed and running in the Github repository that goes with the book. Be sure to download the code from Github.

I've been following this book's development on Github for a while now. I'm super excited it's finally out! It has some great stuff in there that everyone should know (classification, regression, decision trees, SVMs, etc.) and beyond. It uses OpenCV, some Scikit learn and Keras. Python only!

Easy to understand

Micheal's book is intended for starters, undergraduates & PhD students, researchers, primarily in the machine learning or related area.This book will be an essential reference for practitioners of modern machine learning. It covers the basic concepts such as Decision Tree, SVMs, Classification and etc. and the powerful modern computing methods that build on those concepts. I've been following this book on Git for quite a long time and I even forked the original code. It uses the Python Jupyter Notebook to describe concepts in each chapter and also uses the OpenCV, Python Libraries like Scikit-learn and Machine Learning Framework Keras. Both the book and code are quite helpful towards my study. A must-buy for anyone interested in machine learning or curious about how to extract useful knowledge from Computer Vision.

I like this book because it connects three things I really like (ML, OpenCV and Python). Every chapter and subchapter begins with some essential theory and then useful exercises are presented with practical Jupyter's notebooks. I'm going to use material from this book during my lectures on introduction to Machine Learning. If you are interested in Machine Learning and you'd like to know how to combine it with OpenCV, then this is a book for you.

Its Very good book. Its Explained in Deep Detailed Manner and the Codal contents make the Learning Better and Good Narrative of the BOok make it easy for any person to learn and adopt the Learning to Instant apply to Problems.. wish very Best for the Author..

This book has been a great read. Covers all the fundamentals and walks you through the problems step by step. Highly recommended!

I have read several books of machine learning, this seems to me an interesting book on that subject but I do not find a strong relationship with the opencv world;I was expecting it to speak of SSD or RNN, but nothing of all this; cmq is definitely a great book

I’m half way trough. Good book. Programming code has mistakes.

With the price I am paying I expected the quality of the book to be good. Unfortunately, the printing is in black and white and the resolution of the figures are at times hard to interpret especially when contours are involved.Some parameters of the code used is not clearly explained and some codes are not able to replicate.In a nutshell, the book covers only very basic contents of OpenCV. It is not a solid book for advance user but rather for someone at the early stage or wanted to get their feet wet in computer vision. With the price I am paying, the paper quality of the book is just ok, the font size is rather large, printing is in grayscale, therefore it is not the best bang for the buck book for computer vision.

Si bien cubre muy bien el tema de OpenCV, contiene muchisima información valiosa para empezar con sklearn y numpy, breves pero efectivas introducciones de ambos. El libro sustenta con ejemplos claros la teoria, incluye poca pero necesaria math, aunque no abunda tanto en ello sino que va directo al "hands on" casi desde las primeras páginas.Para principiantes como yo en el tema de Machine Learning es un libro excelente, aún no lo termino pero hasta ahora he logrado entender muchos términos que en otros libros daban por hecho y no me permitían avanzar de manera efectiva,Si eres developer y quieres iniciarte con Machine Learning es un primer paso excelente.

Solo explica por encima los conceptos mas básicos y se centra más en los detalles de programación poco importantes (como por ejemplo, como ajustar los datos para pasarlos de una librería a otra), que en OpenCV, los algoritmos que implementa y cuando utilizar uno y otro y como funcionan por debajo.

Good read