Remove Data Lakes Remove ETL Remove Natural Language Processing
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Reducing hallucinations in LLM agents with a verified semantic cache using Amazon Bedrock Knowledge Bases

AWS Machine Learning Blog

Previously, he was a Data & Machine Learning Engineer at AWS, where he worked closely with customers to develop enterprise-scale data infrastructure, including data lakes, analytics dashboards, and ETL pipelines.

AWS 119
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Beyond data: Cloud analytics mastery for business brilliance

Dataconomy

Text analytics: Text analytics, also known as text mining, deals with unstructured text data, such as customer reviews, social media comments, or documents. It uses natural language processing (NLP) techniques to extract valuable insights from textual data. Ensure that data is clean, consistent, and up-to-date.

Analytics 203
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Build an automated insight extraction framework for customer feedback analysis with Amazon Bedrock and Amazon QuickSight

AWS Machine Learning Blog

Businesses can use LLMs to gain valuable insights, streamline processes, and deliver enhanced customer experiences. In the first step, an AWS Lambda function reads and validates the file, and extracts the raw data. The Step Functions workflow starts.

AWS 126
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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.

AI 128
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Cepsa Química improves the efficiency and accuracy of product stewardship using Amazon Bedrock

AWS Machine Learning Blog

He is currently leading the Data, Advanced Analytics & Cloud Development team in the Digital, IT, Transformation & Operational Excellence department at Cepsa Química, with a focus in feeding the corporate data lake and democratizing data for analysis, machine learning projects, and business analytics.

AWS 118
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How to Effectively Handle Unstructured Data Using AI

DagsHub

Social media conversations, comments, customer reviews, and image data are unstructured in nature and hold valuable insights, many of which are still being uncovered through advanced techniques like Natural Language Processing (NLP) and machine learning. Tools like Unstructured.io

AI 52
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Exploring the AI and data capabilities of watsonx

IBM Journey to AI blog

This allows users to accomplish different Natural Language Processing (NLP) functional tasks and take advantage of IBM vetted pre-trained open-source foundation models. Encoder-decoder and decoder-only large language models are available in the Prompt Lab today. To bridge the tuning gap, watsonx.ai

AI 74