The lectures will introduce interested PhD students to the advanced machine learning topics as deep learning with applications.

Place: Oeste Lab OL5 - Edificio Politécnico

https://www.google.com/maps/dir//40.512869,-3.348754

1. Machine Learning - starting pack

-     Machine Learning concepts : Learning paradigms (supervised, unsupervised, self-supervised), Foundations concepts (training, testing and validation), Learning objectives( generalisation Vs. overfitting/underfitting, Loss Function)

-     Types of Machine Learning (Classification Vs. Clustering, regression linear/logistic, Neural networks, Other algorithms)

2. Deep Learning algorithms and techniques (Introduction to deep learning, CNN, AE vs. PCA ,VAE, GAN, Reinforcement Learning)

3. Focusing on Applications (Examples of DL applied to Computer vision for surveillance, healthcare, cultural heritage, etc.)

The course will be taught by researchers from University of Udine (Itally), Dr. Matteo Dunnhofer a Giner de los Rios visiting fellow and Prof. Dr. Christian Micheloni, together with Prof. Alfredo Gardel (UAH) (alfredo.gardel@uah.es)

Course participation and activities follow-up. Final quizz assessment.