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Explaining neural networks

Difficulty level

Explaining neural networks -  Day 14 lecture of the  Foundations of Machine Learning in Python course.

High-Performance Computing and Analytics Lab, University of Bonn

Topics covered in this lesson
  • Linear classifiers
    • Interpretation by examination
    • Case Study: Deepfake detection
  • Input Optimization
    • The problem with deep CNN
    • Saliency Maps and Integrated Gradients
  • Literature