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INAF SCHOOL OF AI

14–17 Apr 2026
INAF Astronomical Observatory of Capodimonte (Naples)
Europe/Rome timezone

Session

Introduction

14 Apr 2026, 14:30
Auditorium Nazionale Ernesto Capocci (INAF Astronomical Observatory of Capodimonte (Naples))

Auditorium Nazionale Ernesto Capocci

INAF Astronomical Observatory of Capodimonte (Naples)

Description

Participants will learn how to approach, visualize, and understand complex datasets using powerful dimensionality reduction techniques (like PCA and t-SNE). The afternoon is dedicated to the critical steps of data preprocessing, focusing on cleaning, normalization, transformation, and strategies for handling missing data (imputation).

Presentation materials

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  1. 25. Introduction to Machine Learning
    Dr Simone Riggi (INAF - Osservatorio Astrofisico di Catania)
    14/04/2026, 14:30
    • Introduction
    • Big data projects in astronomy
    • What is ML and how do we use it in astronomy?
    • Regression & highlights
    • Classification & highlights
    • Anomaly detection & highlights
    • Object detection & highlights
    • Forecasting & highlights
    • Data preprocessing & generation & highlights
    • Outlier detection
    • Simple methods (e.g. IQR-based)
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  2. 26. Data basics & formats
    Farida Farsian (Istituto Nazionale di Astrofisica (INAF))
    14/04/2026, 15:00
    • Data properties (5Vs, format, modality, dimensionality, etc)
    • Tabular data formats most used in Astrophysics
    • Ascii/csv
    • ROOT
    • FITS
    • HDF5/NetCDF
    • VO tables
    • Parquet
    • Relational DB
    • Data I/O considerations
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  3. 27. Data Cleaning
    Dr Simone Riggi (INAF - Osservatorio Astrofisico di Catania)
    14/04/2026, 16:10
    • Data consistency checks
    • Data visualization
    • Examples of 1D data visualization: pie/bar/graph/histogram
    • Examples of 2D visualization: scatter plots, 2D histograms (lego, contour, color maps)
    • Examples of 3D visualization: volume renderings, iso surface, slicing planes
    • Examples of ND data visualization: correlation, scatter plots
    • Dimensionality reduction: curse of...
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  4. 28. Data Transformation
    Farida Farsian (Istituto Nazionale di Astrofisica (INAF))
    14/04/2026, 17:10
    • Tabular data pre-processing
    • Linear transforms: minmax normalization, standardization, scaling
    • Non-linear transforms: power/log, Box-Cox, Yeo-Johnson, Quantile
    • Transforming categorical data
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  5. 31. Tutorial - Data Cleaning & Transformation
    Farida Farsian (Istituto Nazionale di Astrofisica (INAF)), Dr Simone Riggi (INAF - Osservatorio Astrofisico di Catania)
    14/04/2026, 17:40
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