Practicing trustworthy machine learning : consistent, transparent, and fair AI pipelines

By:

Pruksachatkun, Yada

Contributor(s):

Material type: Text

9789355422194

Subject(s):

DDC classification:

006.31 PRU-P

Contents:

1. Privacy 2. Fairness and bias 3. Model explainability and interpretability 4. Robustness 5. Secure and trustworthy data generation 6. More state-of-the-art research questions 7. From theory to practice 8. An ecosystem of trust A. Synthetic data generation tools B. Other interpretability and explainability tool kits

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Books	IIITD General Stacks	Computer Science and Engineering	006.31 PRU-P (Browse shelf(Opens below))	Available		012498

Total holds: 0

This book includes an index.

1. Privacy 2. Fairness and bias
3. Model explainability and interpretability
4. Robustness
5. Secure and trustworthy data generation
6. More state-of-the-art research questions

7. From theory to practice 8. An ecosystem of trust
A. Synthetic data generation tools
B. Other interpretability and explainability tool kits

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