INAF SCHOOL OF AI

Session

Supervised Learning

15 Apr 2026, 09:30

Auditorium Nazionale Ernesto Capocci (INAF Astronomical Observatory of Capodimonte (Naples))

Description

We dive into Supervised Learning, exploring how to train models using labeled data. The session covers the core methodology, including train/test/validation splitting and the essential metrics used to evaluate classification and regression models. This is followed by an exploration of classic ML algorithms.

12. Supervised Learning Part I - Theory

Dr Stefano Cavuoti (INAF - Astronomical Observatory of Capodimonte Napoli)

15/04/2026, 09:30

theoretical introduction to supervised learning key concepts:

• scaling
• hyper parameter tuning
• train-validation-test split
• cross validation
• classification and regression metrics
• feature importance

the following models will be introduced as well:

• k-nn
• Decision Trees (DT)
• Random Forests (RF)
• Support Vector Machines (SVM)

13. Supervised Learning Part I - hands-on session

Dr Stefano Cavuoti (INAF - Astronomical Observatory of Capodimonte Napoli)

15/04/2026, 11:30

19. Supervised Learning Part II - Theory and Hands-on session

Giuseppe Angora (Istituto Nazionale di Astrofisica (INAF))

15/04/2026, 14:15

1) Theoretical introduction to Supervised Learning key concepts:

• Perceptron
• Multi Layer Perceptron
• Activation Functions
• Cost Functions
• Optmizers
• Regularization techniques
• Convolutional Neural Network
  • Convolution
  • Pooling
  • building CNNs
  • CNN examples: VGG, ResNet, Inception
• Convolutional Autoencoder
  The lesson includes code...

30. Supervised Learning Part II - Hands-on

Giuseppe Angora (Istituto Nazionale di Astrofisica (INAF))

15/04/2026, 16:00

Please refer to 'Supervised Learning Part II - Theory' in order to download materials as well as to the contribution description