Raffaella Lanzarotti

Schedule of Classes (A.Y. 2019-2020)

5th February, 10:30 - 13:30. Lab 3rd Floor

10th February, 10:30 - 13:30. Lab 3rd Floor

12th February, 10:30 - 13:30. Lab 3rd Floor

17th February, 10:30 - 13:30. Room TAU

Last lesson: TO BE DEFINED

---

Aim

The course aims at introducing deep learning from a theoretical point of view, specifying the peculiarities of several architectures such as Deep Feedforward Networks, Convolutional Networks, Recurrent and Recursive Nets, Autoencoders and GANs. As a case study, systems for processing and understanding images and videos representing human faces will be presented and analized.

Date	Topic	Slides	Code
5/2/2020	Introduction to Machine Learning	Class1	Lab1
10/2/2020	Deep Sequence Modeling	Class2	Lab2
10/2/2020	Deep Learning for Computer Vision	Class3	Lab3
12/2/2020	Deep Generative Models	Class4	Lab4
12/2/2020	Reinforcement Learning	Class5
12/2/2020	Deep Learning: Limitations and new frontiers	Class6