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Evaluate Generative AI Apps with Azure AI Studio

In this session, we will explore how to evaluate generative AI applications using the powerful tools provided by Azure AI Studio. Azure AI Studio offers a robust platform for evaluating generative AI applications, enabling developers to measure performance, quality, and safety through both automated and custom evaluations. Users can upload datasets, configure test flows, and utilize built-in metrics such as coherence, relevance, and safety assessments. The evaluation process includes steps to set up datasets, choose appropriate metrics, and analyze results through the platform's UI. Azure AI Studio also supports risk evaluations for harmful content, using pre-trained models like GPT-4 to ensure AI-generated content is both effective and safe.
 

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Instructed by

Naveen Kumar M
AVP Software Engineer

Naveen Kumar M is a seasoned Software Engineer with over 13 years of expertise in ETL development, data warehousing, and database design. Currently at Bank of America, Naveen specializes in creating and optimizing ETL processes using SSIS, MS SQL Server, T-SQL, and Azure Data Factory, aligning technical solutions with critical business needs. Formerly a Technical Lead and Senior Principal Software Engineer at Accion Labs, Naveen successfully led complex, multi-stakeholder projects with a focus on SSIS, Informatica ETL, Scrum methodologies, and quality management. Recognized with multiple awards for his commitment to excellence and customer satisfaction, Naveen remains a self-motivated, results-oriented professional with a passion for continuous learning and technological innovation.

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