Explore face detection models in Python and compare their results in this comprehensive live coding session. Dive into various aspects of facial analysis, including age estimation, race classification, emotion recognition, and keypoint detection. Learn to implement and utilize popular libraries such as Deepface, Dlib, and Mediapipe Facemesh. Follow along as the instructor demonstrates practical applications like creating a photobooth, analyzing face similarity, and performing demographic analysis. Gain hands-on experience with different face detection techniques and understand their strengths and limitations. By the end of this tutorial, you'll have a solid foundation in implementing face detection algorithms and be able to apply them to your own projects.