Description: Platform and Model Design for Responsible AI by Amita Kapoor, Sharmistha Chatterjee Estimated delivery 3-12 business days Format Paperback Condition Brand New Description Craft ethical AI projects with privacy, fairness, and risk assessment features for scalable and distributed systems while maintaining explainability and sustainabilityPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesLearn risk assessment for machine learning frameworks in a global landscapeDiscover patterns for next-generation AI ecosystems for successful product designMake explainable predictions for privacy and fairness-enabled ML trainingBook DescriptionAI 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, its necessary to build an explainable, responsible, transparent, and trustworthy AI-enabled system. With Platform and Model Design for Responsible AI, youll be able to make existing black box models transparent.Youll 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. Youll start by designing ethical models for traditional and deep learning ML models, as well as deploying them in a sustainable production setup. After that, youll 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. Youll then build a fair and private ML model with proper constraints, tune the hyperparameters, and evaluate the model metrics.By the end of this book, youll know the best practices to comply with data privacy and ethics laws, in addition to the techniques needed for data anonymization. Youll be able to develop models with explainability, store them in feature stores, and handle uncertainty in model predictions.What you will learnUnderstand the threats and risks involved in ML modelsDiscover varying levels of risk mitigation strategies and risk tiering toolsApply traditional and deep learning optimization techniques efficientlyBuild auditable and interpretable ML models and feature storesUnderstand the concept of uncertainty and explore model explainability toolsDevelop models for different clouds including AWS, Azure, and GCPExplore ML orchestration tools such as Kubeflow and Vertex AIIncorporate privacy and fairness in ML models from design to deploymentWho this book is forThis 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. Author Biography Amita Kapoor is an accomplished AI consultant and educator, with over 25 years of experience. She has received international recognition for her work, including the DAAD fellowship and the Intel Developer Mesh AI Innovator Award. She is a highly respected scholar in her field, with over 100 research papers and several best-selling books on deep learning and AI. After teaching for 25 years at the University of Delhi, Amita took early retirement and turned her focus to democratizing AI education. She currently serves as a member of the Board of Directors for the non-profit Neuromatch Academy, fostering greater accessibility to knowledge and resources in the field. Following her retirement, Amita also founded NePeur, a company that provides data analytics and AI consultancy services. In addition, she shares her expertise with a global audience by teaching online classes on data science and AI at the University of Oxford. Sharmistha Chatterjee is an evangelist in the field of machine learning (ML) and cloud applications, currently working in the BFSI industry at the Commonwealth Bank of Australia in the data and analytics space. She has worked in Fortune 500 companies, as well as in early-stage start-ups. She became an advocate for responsible AI during her tenure at Publicis Sapient, where she led the digital transformation of clients across industry verticals. She is an international speaker at various tech conferences and a 2X Google Developer Expert in ML and Google Cloud. She has won multiple awards and has been listed in 40 under 40 data scientists by Analytics India Magazine (AIM) and 21 tech trailblazers in 2021 by Google. She has been involved in responsible AI initiatives led by Nasscom and as part of their DeepTech Club. Details ISBN 1803237074 ISBN-13 9781803237077 Title Platform and Model Design for Responsible AI Author Amita Kapoor, Sharmistha Chatterjee Format Paperback Year 2023 Pages 516 Publisher Packt Publishing Limited GE_Item_ID:141993264; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. 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Price: 69.8 USD
Location: Fairfield, Ohio
End Time: 2024-11-21T07:26:51.000Z
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Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
ISBN-13: 9781803237077
Book Title: Platform and Model Design for Responsible AI
Number of Pages: 516 Pages
Language: English
Publication Name: Platform and Model Design for Responsible AI : Design and Build Resilient, Private, Fair, and Transparent Machine Learning Models
Publisher: Packt Publishing, The Limited
Subject: General, Data Visualization
Publication Year: 2023
Type: Textbook
Subject Area: Computers, Science
Item Length: 92.5 in
Author: Sharmistha Chatterjee, Amita Kapoor
Item Width: 75 in
Format: Trade Paperback
