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Go vs. Python for Modern Data Workflows: Need Help Deciding?

KDnuggets

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter Go vs. Python for Modern Data Workflows: Need Help Deciding?

Python 294
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Data Engineering for IoT Applications: Unleashing the Power of the Internet of Things

Data Science Connect

A recent article on Analytics Insight explores the critical aspect of data engineering for IoT applications. Understanding the intricacies of data engineering empowers data scientists to design robust IoT solutions, harness data effectively, and drive innovation in the ever-expanding landscape of connected devices.

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Reducing hallucinations in LLM agents with a verified semantic cache using Amazon Bedrock Knowledge Bases

AWS Machine Learning Blog

He specializes in large language models, cloud infrastructure, and scalable data systems, focusing on building intelligent solutions that enhance automation and data accessibility across Amazons operations. Rajesh Nedunuri is a Senior Data Engineer within the Amazon Worldwide Returns and ReCommerce Data Services team.

AWS 127
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Retrieval-Augmented Generation with LangChain, Amazon SageMaker JumpStart, and MongoDB Atlas semantic search

Flipboard

Prior joining AWS, as a Data/Solution Architect he implemented many projects in Big Data domain, including several data lakes in Hadoop ecosystem. As a Data Engineer he was involved in applying AI/ML to fraud detection and office automation. They are available in a variety of sizes and configurations.

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Open Data Lakes, Safeguarding Images From AI, Free Data Viz Tools, and 50% Off ODSC East

ODSC - Open Data Science

The Future of the Single Source of Truth is an Open Data Lake Organizations that strive for high-performance data systems are increasingly turning towards the ELT (Extract, Load, Transform) model using an open data lake.

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Introducing the Amazon Comprehend flywheel for MLOps

AWS Machine Learning Blog

Solution overview Amazon Comprehend is a fully managed service that uses natural language processing (NLP) to extract insights about the content of documents. MLOps requires the integration of software development, operations, data engineering, and data science. Each flywheel has its own dedicated data lake.

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6 Remote AI Jobs to Look for in 2024

ODSC - Open Data Science

Data Engineer Data engineers are responsible for the end-to-end process of collecting, storing, and processing data. They use their knowledge of data warehousing, data lakes, and big data technologies to build and maintain data pipelines.