fairhopeweb / hands-on-machine-learning-with-opencv-4

Hands-On Machine Learning with OpenCV 4, Published by Packt

Hands-On Machine Learning with OpenCV 4 [Video]Hands-On Machine Learning with OpenCV 4 [Video]

This is the code repository for Hands-On Machine Learning with OpenCV 4 [Video]Hands-On Machine Learning with OpenCV 4 [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.

About the Video Course

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.

What You Will Learn

• How to build real-world Computer Vision applications.
• Deploy Face and Eyes Detection with HAAR Cascade Classifiers.
• Recognize Age, Gender and Emotions and Roadside Landmarks.
• Develop Fast QR Code Detection and Decoding application.
• Create DNN based Image Classifier.
• Train an Object Detection Model and Detect Persons, and Vehicles.

Instructions and Navigation

Assumed Knowledge

To fully benefit from the coverage included in this course, you will need:
This course can be used as a generic resource to bridge the gap from beginner to mastering computer vision implementations in machine learning. Basic knowledge of Python is expected.

Technical Requirements

This course has the following software requirements:
Recommended Hardware Requirements For an optimal experience with hands-on labs and other practical activities, we recommend the following configuration:

OS: Unix Based (MacOS or Linux) Processor: >=Intel i5 Memory: 8GB Storage: >=128GB

Software Requirements Operating system: Unix-based (MacOS or Linux) Browser: Chrome/Firefox/Safari Atom/Sublime/VS Code Python 3.7 installed

Related Products

• Hands-On OpenCV 4 with Python [Video]Hands-On OpenCV 4 with Python [Video]

• Hands-On Machine Learning with TensorFlow.js [Video]

• OpenCV 4 Computer Vision with Python Recipes [Video]OpenCV 4 Computer Vision with Python Recipes [Video]