Analyzing and Transforming Faces in Python
Beginner
50 Lessons
15h
Certificate of Completion
Takeaway Skills
A strong understanding of the basics of facial recognition
A working knowledge of three unique machine learning libraries: MediaPipe, Dlib, and DeepFace
A deep familiarity with common facial analysis techniques using Python
The ability to use deep neural networks to identify age, gender, race, and emotion from facial expressions
The ability to apply various artistic effects to faces
A complete perspective on facial recognition models and the tools to build a multifaceted model to common facial analysis tasks
Hands-on experience with Python, MediaPipe, Dlib, and DeepFace for facial analysis
Course Overview
Face analysis technology is a rapidly growing biometric software discipline with wide-ranging applications in surveillance, forensics, game design, and social media. As with other machine learning domains, Python has several libraries for computer vision, image analysis, and pattern recognition that make it ideal for facial analysis. This course is a hands-on introduction to facial recognition with three unique libraries—MediaPipe, Dlib, and DeepFace. You’ll start with face detection, landmarking, and face...Show More
Course Content
Introduction
Core Functions
Predictive Analytics
Manipulation Functions
Virtual Makeover Functions
Face Recognition
5 Lessons
Conclusion
1 Lesson
Appendices
2 Lessons
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