General Information
SSD: ING-INF/05
CFU: 6
Lecturer: Eliana Pastor
Teaching Staff: Gabriele Ciravegna, Eleonora Poeta
Information:
Dear Students,
Please note that due to an institutional event, there will be no lecture tomorrow, March 17.
Schedule
- Monday, 8:30-10:00 – classroom 11T
- Thursday, 8:30-10:00 – classroom 5T
- Friday, 8:30-10:00 – classroom 2I
Teaching material
- Course introduction (slides)
- Trustworthy AI: definition and motivations (slides)
- Explainable AI: taxonomy (slides)
- Pre-modeling explainability (slides)
- In-modeling explainability (slides)
- Post-hoc model agnostic – global (slides)
- Post-hoc model agnostic – local surrogate models (slides)
- Post-hoc model agnostic – local – explaining by removing/perturbing (slides)
Laboratory material
- Lab 0.1: Machine Learning pipeline with Pandas and Scikit-learn (zip) (zip_solution) (pdf_solution)
- Lab 0.2: Introduction to Deep Learning with PyTorch (zip)
- Lab 1: Interpretable by-design (zip) (zip_solution) (pdf_solution)
- Lab 2: Post-hoc global explanation methods (zip) (zip_solution) (pdf_solution)
- Lab 3a: Post-hoc Local explanation methods – LIME (zip)