000			01100nam a22002417a 4500
003			IIITD
005			20240111145415.0
008			231215b xxu||||| |||| 00| 0 eng d
020			_a9789355422194
040			_aIIITD
082			_a006.31 _bPRU-P
100			_aPruksachatkun, Yada
245			_aPracticing trustworthy machine learning : _bconsistent, transparent, and fair AI pipelines _cby Yada Pruksachatkun, Matthew McAteer, and Subhabrata Majumdar.
260			_bO'Reilly, _aMumbai : _c©2023
300			_axxiv, 274 p. : _bill, ; _c23 cm.
504			_aThis book includes an index.
505			_t1. Privacy _t2. Fairness and bias _t3. Model explainability and interpretability _t4. Robustness _t5. Secure and trustworthy data generation _t6. More state-of-the-art research questions _t7. From theory to practice _t8. An ecosystem of trust _tA. Synthetic data generation tools _tB. Other interpretability and explainability tool kits
650			_aMachine learning
650			_aPrivacy
700			_a McAteer, Matthew
700			_aMajumdar, Subhabrata
942			_2ddc _cBK
999			_c171966 _d171966