This repository collects the laboratory material of the Explainable and Trustworthy AI Course.
Lecturer: Eliana Pastor
Teaching Staff: Elena Baralis, Gabriele Ciravegna, Salvatore Greco, Eleonora Poeta
0.1 Machine Learning pipeline with Pandas and Scikit-learn
0.2: Introduction to PyTorch with Deep Learning
Interpretable by design
Post-hoc global explanation methods
Post-hoc Local explanation methods – LIME
Post-hoc Local explanation methods – SHAP
Concept-based XAI
6a - Introduction to NLP with HuggingFace
6b - Explainable NLP