Remove Business Intelligence Remove Prompt Engineering Remove Responsible AI
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Evolving Trends in Data Science: Insights from ODSC Conference Sessions from 2015 to 2024

ODSC - Open Data Science

Tools like Python , R , and SQL were mainstays, with sessions centered around data wrangling, business intelligence, and the growing role of data scientists in decision-making. Simultaneously, concerns around ethical AI , bias , and fairness led to more conversations on Responsible AI.

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Build an automated insight extraction framework for customer feedback analysis with Amazon Bedrock and Amazon QuickSight

AWS Machine Learning Blog

With Amazon Bedrock, developers can experiment, evaluate, and deploy generative AI applications without worrying about infrastructure management. Its enterprise-grade security, privacy controls, and responsible AI features enable secure and trustworthy generative AI innovation at scale.

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Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning Blog

Fourth, we’ll address responsible AI, so you can build generative AI applications with responsible and transparent practices. Fifth, we’ll showcase various generative AI use cases across industries. Leave the session inspired to bring Amazon Q Apps to supercharge your teams’ productivity engines.

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Analyze customer reviews using Amazon Bedrock

AWS Machine Learning Blog

Amazon Bedrock is a fully managed service that offers a choice of high-performing FMs from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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How Twilio generated SQL using Looker Modeling Language data with Amazon Bedrock

AWS Machine Learning Blog

RAG optimizes language model outputs by extending the models’ capabilities to specific domains or an organization’s internal data for tailored responses. This post highlights how Twilio enabled natural language-driven data exploration of business intelligence (BI) data with RAG and Amazon Bedrock.

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