Explaining neural networks
Explaining neural networks
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
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