Deep Learning course

In this course I had to sumbit 2 course works which included experimenting with different neural network architectures, such as

• convolutional,
• recurrent,
• graph message passing,
• autoencoder,
• generative adversarial networks and
• physics informed networks.

All the code for running these models are in two repositories, the reports can be found in the root of the repositories. Project 1 and Project 2.