Emotion AI: Facial Key-points Detection

About this guided project

In this 1-hour long project-based course, you will be able to: - Understand the theory and intuition behind Deep Learning, Convolutional Neural Networks (CNNs) and Residual Neural Networks. - Import Key libraries, dataset and visualize images. - Perform data augmentation to increase the size of the dataset and improve model generalization capability. - Build a deep learning model based on Convolutional Neural Network and Residual blocks using Keras with Tensorflow 2.0 as a backend. - Compile and fit Deep Learning model to training data. - Assess the performance of trained CNN and ensure its generalization using various KPIs. - Improve network performance using regularization techniques such as dropout.

What skills will you gain?

Tensorflow

Artificial Neural Networks

Deep Learning

Machine Learning

Applied Machine Learning

Artificial Intelligence and Machine Learning (AI/ML)

Keras (Neural Network Library)

Artificial Intelligence

Computer Vision