Remove AI Modeling Remove ETL Remove Prompt Engineering
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30% Off ODSC East, Fan-Favorite Speakers, Foundation Models for Times Series, and ETL Pipeline…

ODSC - Open Data Science

30% Off ODSC East, Fan-Favorite Speakers, Foundation Models for Times Series, and ETL Pipeline Orchestration The ODSC East 2025 Schedule isLIVE! Explore the must-attend sessions and cutting-edge tracks designed to equip AI practitioners, data scientists, and engineers with the latest advancements in AI and machine learning.

ETL 52
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Ivo Everts, Databricks: Enhancing open-source AI and improving data governance

AI News

. “From a quality standpoint, we believe that DBRX is one of the best open-source models out there and when we refer to ‘best’ this means a wide range of industry benchmarks, including language understanding (MMLU), Programming (HumanEval), and Math (GSM8K).”

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Evaluate large language models for your machine translation tasks on AWS

AWS Machine Learning Blog

It is critical for AI models to capture not only the context, but also the cultural specificities to produce a more natural sounding translation. The solution proposed in this post relies on LLMs context learning capabilities and prompt engineering. the natural French translation would be very different.

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50% Off ODSC East 2025 Passes, Prompt Engineering Techniques, AI Builders Week 3 Highlights, and AI…

ODSC - Open Data Science

50% Off ODSC East 2025 Passes, Prompt Engineering Techniques, AI Builders Week 3 Highlights, and AI Guardrails The ODSC East 2025 Preliminary Schedule isLIVE! has unveiled its latest AI model, Qwen 2.5-Max, We discuss the open-source Guardrails AI and how you can use it to safeguard your AIapps.

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

AWS Machine Learning Blog

Model generalization Benefits from exposure to diverse text genres and domains during pre-training, enhancing generalization to new tasks. Operational efficiency Uses prompt engineering, reducing the need for extensive fine-tuning when new categories are introduced. We provide a prompt example for feedback categorization.

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Exploring the AI and data capabilities of watsonx

IBM Journey to AI blog

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise.

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FMOps/LLMOps: Operationalize generative AI and differences with MLOps

AWS Machine Learning Blog

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.