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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning Blog

Without specialized structured query language (SQL) knowledge or Retrieval Augmented Generation (RAG) expertise, these analysts struggle to combine insights effectively from both sources. Use Amazon Athena SQL queries to provide insights. The AWS infrastructure has already been deployed as part of the CloudFormation template.

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What is Snowpark — and Why Does it Matter? A phData Perspective

phData

Snowpark is the set of libraries and runtimes in Snowflake that securely deploy and process non-SQL code, including Python , Java, and Scala. As a declarative language, SQL is very powerful in allowing users from all backgrounds to ask questions about data. What is Snowflake’s Snowpark? Why Does Snowpark Matter?

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Top 10 Generative AI Companies Revealed

Towards AI

PwC 👉Industry domain: AI, Professional services, Business intelligence, Consulting, Cybersecurity, Generative AI 👉Location: 73 offices 👉Year founded: 1998 👉Programming Languages Deployed: Java, Google Cloud, Microsoft SQL, jQuery, Pandas, R, Oracle 👉Benefits: Hybrid workspace, Child care and parental leave, flexible (..)

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How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Flipboard

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning.

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Michael I. Jordan of Berkeley on Learning-Aware Mechanism Design

ODSC - Open Data Science

Rumelhart Prize in 2015, and the ACM/AAAI Allen Newell Award in 2009. He received the Ulf Grenander Prize from the American Mathematical Society in 2021, the IEEE John von Neumann Medal in 2020, the IJCAI Research Excellence Award in 2016, the David E.

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Prepare your data for Amazon Personalize with Amazon SageMaker Data Wrangler

AWS Machine Learning Blog

It has over 300 preconfigured data transformations as well as the ability to bring in custom code to create custom transformations in PySpark, SQL, and a variety of data processing libraries, such as pandas. ACM Transactions on Interactive Intelligent Systems (TiiS) 5, 4, Article 19 (December 2015), 19 pages. DOI= [link]

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Analyzing the history of Tableau innovation

Tableau

Incredible growth started in 2005 with the company roughly doubling in size every year until 2015. Query allowed customers from a broad range of industries to connect to clean useful data found in SQL and Cube databases. The first Tableau customer conference was in 2008. Tableau had its IPO at the NYSE with the ticker DATA in 2013.

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