Emotion AI: Facial Key-points Detection

Overview

Embark on a captivating journey into the world of AI with our project-based course, "Emotion AI:

Facial Key-points Detection". This comprehensive 1-hour course is designed for individuals eager to dive deep into the fascinating realms of Deep Learning, Convolutional Neural Networks (CNNs), and Residual Neural Networks.

Offered on Coursera, this course is perfect for anyone looking to gain a robust understanding of the theory and intuition driving these advanced technologies.

Throughout this course, participants will:

• Gain insights into the foundational theories guiding Deep Learning, CNNs, and Residual Neural Networks.
• Learn to import key libraries, datasets, and how to visualize images effectively.
• Explore data augmentation techniques to expand the dataset size, enhancing the model's ability to generalize.
• Develop a sophisticated deep learning model utilizing Convolutional Network and Residual blocks through Keras, integrated with Tensorflow 2.0.
• Compile and fit the Deep Learning model to training data, ensuring thorough learning.
• Evaluate the performance of the trained CNN, using various Key Performance Indicators (KPIs) to ensure its generalization.
• Implement regularization techniques such as dropout to boost network performance.

This course falls under several key categories, including Computer Vision Courses, Deep Learning Courses, and Facial Recognition Courses, making it a perfect match for individuals looking to specialize in these cutting-edge areas. Don't miss this opportunity to enhance your skills and knowledge in facial key-point detection through Deep Learning methodologies provided by Coursera.

Taught by

Ryan Ahmed

Subjects