$125 | Duration: 2h 3m | Video: h264, 1280x720 | Audio: AAC, 44kHz, 2 Ch | 411 MB
Genre: eLearning | Language: English | December 31, 2018

Expand your OpenCV knowledge and use machine learning to your advantage with this practical hands-on course!

Video Description
Computer Vision has been booming in the past few years and it has become a highly sought-after skill. There are tons of real-life problems for which Machine Learning-based solutions provide significantly better results than traditional ad-hoc approaches. The application of Machine Learning and Deep Learning is rapidly gaining significance in Computer Vision.

All the latest tech-from self-driving cars to autonomous drones-uses AI running on images and videos. If you want to get your hands dirty with this technology and use it to craft your own unique solutions, then look no further because this course is perfect for you!

This hands-on course will immerse you in Machine Learning, and you'll learn about key topics and concepts along the way. This course is perfect for people who wish to explore the possibilities inherent in Machine Learning.

The code bundle for this course is available at - https://github.com/PacktPublishing/Hands-On-Machine-Learning-with-OpenCV-4

Style and Approach
Its hands-on, practical approach ensures that this course is never boring and that the viewer learns through interactive examples and apps. All necessary information is conveyed as and when required, with an emphasis on where to apply it in real life. One key concept is covered in every video, along with a sample code snippet to demonstrate its usage. The course builds its way up and gradually moves from Machine Learning to Deep Learning techniques.

Table of Contents
COURSE OVERVIEW AND INTRODUCTION
BASICS OF IMAGE PROCESSING USING OPENCV
MACHINE LEARNING ON IMAGES: THE SUPERVISED APPROACH - KNNS AND SVMS
THE UNSUPERVISED APPROACH - CLUSTERING WITH K-MEANS
OBJECT DETECTION USING HISTOGRAMS AND HAAR CASCADES
CONVOLUTIONAL NEURAL NETWORKS FOR OBJECT DETECTION
TRAINING A CNN TO DETECT CUSTOM OBJECTS

What You Will Learn
Become more experienced with using OpenCV and its vast in-built functionalities
Apply various Machine Learning algorithms to real-life problems
Explore Supervised Learning and Unsupervised Learning approaches in Computer Vision
Master the standard template/pipeline while designing ML solutions
Work with various datasets and visualize them
Get familiar with multiple ways to perform real-time object detection
Train your own custom image classifier using Convolutional Neural Networks
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