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TAI
General
TAI Assignment
Establishing the rules for building trustworthy AI
THEORETICAL PART
PRACTICAL PART - Introduction to Statistical Learning models (Rec)
PRACTICAL PART - Model Selection (Rec)
PRACTICAL PART - Introduction to Machine Learning Models (Rec)
PRACTICAL PART - Python Practice 1 (Statistical and Machine Learning Models - Model Selection) (Rec)
PRACTICAL PART - Explainability of Artificial Intelligence methods (LIVE)
PRACTICAL PART - Reading Scientific Paper 1
PRACTICAL PART - Accuracy of Artificial Intelligence methods (Rec)
PRACTICAL PART - Python Practice 2 (Explainability and Accuracy of AI) (LIVE)
PRACTICAL PART - Reading Scientific Paper 2
PRACTICAL PART - S.A.F.E. Artificial Intelligence (Rec)
Realizing Trustworthy AI solutions for diagnosis and prognosis support
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Calendar
Trustworthy AI
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Courses
Ethical and Legal Considerations
TAI
PRACTICAL PART - Python Practice 1 (Statistical and Machine Learning Models - Model Selection) (Rec)
Statistical and Machine Learning Models - Application in Python (Session 5)
Statistical and Machine Learning Models - Application in Python (Session 5)
Datasets
babies.csv
diabetes_binary.csv
Jupyter notebooks
Linear Regression.ipynb
Logistic Regression.ipynb
Tree models and model selection.ipynb
Video Lessons.docx
Video Lessons.pdf
Download folder
◄ Neural Network and tree models (Session 4)
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Announcements
TAI Assignment
TAI Practical Part - E. Raffinetti
Trustworthy AI Framework
Data Management
Trustworthy AI™ - Bridging the ethics gap surrounding AI
Recorded lectures
Syllabus and Session Outlines
Introduction (Session 1)
Linear Regression Models (Session 1)
Logistic Regression Models (Session 2)
Model Selection (Session 3)
Neural Network and tree models (Session 4)
The Explainability principle (Session 6) - Session Scheduled on Wednesday 12 April 2023 - 6:00-8:30 p.m. The Zoom link is available in Moodle Calendar.
First Reading - Paper: Lorenz Model Selection (Session 7)
The Accuracy principle (Session 8)
Explainability and Accuracy of AI - Application in Python (Session 9) - Session Scheduled on Friday 14 April 2023 - 6:00-8:30 p.m. The Zoom link is now available in Moodle Calendar.
Second Reading - Paper: Explainable AI methods in cyber risk management (Session 10)
The S.A.F.E. score (Session 11)
Realizing Trustworthy AI solutions for diagnosis and prognosis support (Part1 2024)
The Explainability principle (Session 6) - Session Scheduled on Wednesday 12 April 2023 - 6:00-8:30 p.m. The Zoom link is available in Moodle Calendar. ►