{"product_id":"platform-and-model-design-for-responsible-ai-design-and-build-resilient-private-fair-and-transparent-machine-learning-models-paperback","title":"Platform and Model Design for Responsible AI: Design and build resilient, private, fair, and transparent machine learning models - Paperback","description":"\u003cp\u003eby \u003cb\u003eAmita Kapoor\u003c\/b\u003e (Author), \u003cb\u003eSharmistha Chatterjee\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eCraft ethical AI projects with privacy, fairness, and risk assessment features for scalable and distributed systems while maintaining explainability and sustainability\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003ePurchase of the print or Kindle book includes a free PDF eBook\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eKey Features: \u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eLearn risk assessment for machine learning frameworks in a global landscape\u003c\/li\u003e\n\u003cli\u003eDiscover patterns for next-generation AI ecosystems for successful product design\u003c\/li\u003e\n\u003cli\u003eMake explainable predictions for privacy and fairness-enabled ML training\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eBook Description: \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eAI algorithms are ubiquitous and used for tasks, from recruiting to deciding who will get a loan. With such widespread use of AI in the decision-making process, it's necessary to build an explainable, responsible, transparent, and trustworthy AI-enabled system. With Platform and Model Design for Responsible AI, you'll be able to make existing black box models transparent.\u003c\/p\u003e\u003cp\u003eYou'll be able to identify and eliminate bias in your models, deal with uncertainty arising from both data and model limitations, and provide a responsible AI solution. You'll start by designing ethical models for traditional and deep learning ML models, as well as deploying them in a sustainable production setup. After that, you'll learn how to set up data pipelines, validate datasets, and set up component microservices in a secure and private way in any cloud-agnostic framework. You'll then build a fair and private ML model with proper constraints, tune the hyperparameters, and evaluate the model metrics.\u003c\/p\u003e\u003cp\u003eBy the end of this book, you'll know the best practices to comply with data privacy and ethics laws, in addition to the techniques needed for data anonymization. You'll be able to develop models with explainability, store them in feature stores, and handle uncertainty in model predictions.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWhat You Will Learn: \u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eUnderstand the threats and risks involved in ML models\u003c\/li\u003e\n\u003cli\u003eDiscover varying levels of risk mitigation strategies and risk tiering tools\u003c\/li\u003e\n\u003cli\u003eApply traditional and deep learning optimization techniques efficiently\u003c\/li\u003e\n\u003cli\u003eBuild auditable and interpretable ML models and feature stores\u003c\/li\u003e\n\u003cli\u003eUnderstand the concept of uncertainty and explore model explainability tools\u003c\/li\u003e\n\u003cli\u003eDevelop models for different clouds including AWS, Azure, and GCP\u003c\/li\u003e\n\u003cli\u003eExplore ML orchestration tools such as Kubeflow and Vertex AI\u003c\/li\u003e\n\u003cli\u003eIncorporate privacy and fairness in ML models from design to deployment\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWho this book is for: \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eThis book is for experienced machine learning professionals looking to understand the risks and leakages of ML models and frameworks, and learn to develop and use reusable components to reduce effort and cost in setting up and maintaining the AI ecosystem.\u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 516\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1.04 x 9.25 x 7.5 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e April 28, 2023\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":51750425887008,"sku":"9781803237077","price":90.7,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0974\/9764\/5344\/files\/22216a82e989137b40ce714bfcb7dde4.webp?v=1779950089","url":"https:\/\/ebocreations.com\/products\/platform-and-model-design-for-responsible-ai-design-and-build-resilient-private-fair-and-transparent-machine-learning-models-paperback","provider":"The E-Book Oasis LLC","version":"1.0","type":"link"}