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In this Masterclass, let Aakash, CEO of Jovian, introduce you to the growing research field of Explainable Artificial Intelligence in 40 minutes. Explainable AI is a set of tools and frameworks to help you understand and interpret the predictions made by your machine learning models.
00:00 – Introduction and importance
06:03 – Types of explainable AI
12:54 p.m. – LIME
4:16 p.m. – SHAP
7:53 p.m. – PAP
24h09 – Resources
27:32 – Questions and answers
The references:
https://github.com/jphall663/awesome-machine-learning-interpretability
DeepFindr: https://www.youtube.com/watch?vOZJ1IgSgP9E&listPLV8yxwGOxvvovp-j6ztxhF3QcKXT6vORU
Kaggle notebook: https://www.kaggle.com/code/parulpandey/intrepreting-machine-learning-models
Interpretable ML book: https://christophm.github.io/interpretable-ml-book/
InterpretML: https://interpret.ml/
Shap Library: https://github.com/slundberg/shap
Partial dependency graphs: https://www.youtube.com/watch?vuQQa3wQgG_s
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