Machine Learning with Open CV and Python
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Machine Learning with Open CV and Python

Analyze and understand your data with the power and simplicity of Python
3.0 (3 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
42 students enrolled
Created by Packt Publishing
Last updated 4/2017
Current price: $10 Original price: $125 Discount: 92% off
5 hours left at this price!
30-Day Money-Back Guarantee
  • 1.5 hours on-demand video
  • 1 Supplemental Resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Master Logistic Regression and regularization techniques
  • Understand supervised and unsupervised machine learning algorithms
  • Implement OpenCV's functionalities in machine learning algorithms
  • Solve image segmentation problem using K-Means Clustering
  • Get to know the key elements of a neural network and deep learning and its ability to learn
  • Load models trained with popular deep learning libraries such as Caffe
View Curriculum
  • Some understanding of statistical concepts would be helpful, but is not mandatory.

OpenCV is a library of programming functions mainly aimed at real-time computer vision. This course will show you how machine learning is great choice to solve real-word computer vision problems and how you can use the OpenCV modules to implement the popular machine learning concepts.

The video will teach you how to work with the various OpenCV modules for statistical modelling and machine learning. You will start by preparing your data for analysis, learn about supervised and unsupervised learning, and see how to implement them with the help of real-world examples. The course will also show you how you can implement efficient models using the popular machine learning techniques such as classification, regression, decision trees, K-nearest neighbors, boosting, and neural networks with the aid of C++ and OpenCV.

About The Author

Joe Minichino is a computer vision engineer for Hoolux Medical by day and a developer of the NoSQL database LokiJS by night. On weekends, he is a heavy metal singer/songwriter. He is a passionate programmer who is immensely curious about programming languages and technologies and constantly experiments with them. At Hoolux, Joe leads the development of an Android computer vision-based advertising platform for the medical industry.

Born and raised in Varese, Lombardy, Italy, and coming from a humanistic background in philosophy (at Milan's UniversitàStatale), Joe has spent his last 11 years living in Cork, Ireland, which is where he became a computer science graduate at the Cork Institute of Technology.

Joe is also the author of Learning OpenCV 3 Computer Vision with Python, Second Edition also for Packt Publishing.

Who is the target audience?
  • If you have a basic working knowledge of computer vision and OpenCV, and want to perform machine learning with OpenCV, this course is for you.
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Curriculum For This Course
12 Lectures
Introduction to Machine Learning
2 Lectures 09:09

This video gives an overview of the entire course.

Preview 03:01

Learn about machine learning.

The Basics of Machine Learning
Extracting Features and Preparing the Data
2 Lectures 10:25

Extracting features from an image.

Extracting Features
Classifier and Regression
3 Lectures 21:07

Recognize handwritten digits.

Preview 08:37

Detect pictures containing cars. 

Logistic Regression

Detect pictures containing cars.

Normal Bayes Classifier
Decision Trees and Support Vector Machines
2 Lectures 22:14

Operate car detection.

Preview 10:12

Operate face recognition.

Support Vector Machines
Neural Networks
1 Lecture 12:29

Operate flower recognition

Preview 12:29
Unsupervised Learning and Introduction to Deep Learning
2 Lectures 20:07

Operate color quantization.

Preview 05:03

Operate handwritten digit recognition.

Deep Learning
About the Instructor
Packt Publishing
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8,109 Reviews
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