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Platform and model design for responsible AI : design and build resilient, private, fair, and transparent machine learning models /: design and build resilient, private, fair, and transparent machine learning models. (2023)
Record Type:
Book
Title:
Platform and model design for responsible AI : design and build resilient, private, fair, and transparent machine learning models /: design and build resilient, private, fair, and transparent machine learning models. (2023)
Main Title:
Platform and model design for responsible AI : design and build resilient, private, fair, and transparent machine learning models
Table of ContentsRisks and Attacks on ML ModelsThe Emergence of Risk-Averse Methodologies and FrameworksRegulations and Policies Surrounding Trustworthy AIPrivacy Management in Big Data and Model Design PipelinesML Pipeline, Model Evaluation and Handling UncertaintyHyperparameter Tuning, MLOPS, and AutoMLFairness Notions and Fain Data GenerationFairness in Model OptimizationModel ExplainabilityEthics and Model GovernanceThe Ethics of Model AdaptabilityBuilding Sustainable, Enterprise-Grade AI PlatformsSustainable Model Life Cycle Management, Feature Stores, and Model CalibrationIndustry-Wide Use-cases.
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