| Semester | Semester 3 |
|---|---|
| Type | Optional |
| Nature | Choice |
| Credit hour | 6 |
|---|---|
| Total number of hours | 30 |
| Number of hours requiring attendance | 60 |
Prerequisites
Description
From shallow to deep networks, convolutional neural networks, recurrent neural networks, generative networks (stacked denoising autoencoder, variational autoencoder, generative adversarial networks), adversarial samples, reinforcement learning, transfer learning, optimization of deep neural networks (tips & tricks), etc.This course is offered by the MSc "Data Science" and for an advanced level in deep learning. Only second year students can participate and after succesful completion of the course "stochastic models in neurocognition and their statistical inferences" during the first year.