Deep Learning Fundamentals

Description

Recommended: Familiarity algorithms

This course focuses on Deep learning concepts including convolutional neural networks, recurrent neural networks, autoencoders, Generative Adversarial Networks (GAN) and their implementation.

The implementation of these algorithms will be based on state-of-the-art industry tools such as TensorFlow 2.0/Keras or Pytorch frameworks.

All students are required to implement the above Deep Learning architectures in a real-world example in the final project/signature assignment.