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MLFlow Mastery: A Complete Guide to Experiment Tracking and Model Management

KDnuggets

By Jayita Gulati on June 23, 2025 in Machine Learning Image by Editor (Kanwal Mehreen) | Canva Machine learning projects involve many steps. It manages the entire machine learning lifecycle. It also works with cloud services like AWS SageMaker. Keeping track of experiments and models can be hard.

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Transcribe, translate, and summarize live streams in your browser with AWS AI and generative AI services

AWS Machine Learning Blog

However, as the reach of live streams expands globally, language barriers and accessibility challenges have emerged, limiting the ability of viewers to fully comprehend and participate in these immersive experiences. The extension delivers a web application implemented using the AWS SDK for JavaScript and the AWS Amplify JavaScript library.

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Unlocking the power of Model Context Protocol (MCP) on AWS

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If youre an AI-focused developer, technical decision-maker, or solution architect working with Amazon Web Services (AWS) and language models, youve likely encountered these obstacles firsthand. The MCP is an open standard that creates a universal language for AI systems to communicate with external data sources, tools, and services.

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Build an Amazon Bedrock based digital lending solution on AWS

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This post demonstrates how you can gain a competitive advantage using Amazon Bedrock Agents based automation of a complex business process. The loan handler AWS Lambda function uses the information in the KYC documents to check the credit score and internal risk score. AWS CDK : 2.143.0

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Syngenta develops a generative AI assistant to support sales representatives using Amazon Bedrock Agents

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Syngenta and AWS collaborated to develop Cropwise AI , an innovative solution powered by Amazon Bedrock Agents , to accelerate their sales reps’ ability to place Syngenta seed products with growers across North America. The collaboration between Syngenta and AWS showcases the transformative power of LLMs and AI agents.

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Principal Financial Group uses QnABot on AWS and Amazon Q Business to enhance workforce productivity with generative AI

AWS Machine Learning Blog

With the QnABot on AWS (QnABot), integrated with Microsoft Azure Entra ID access controls, Principal launched an intelligent self-service solution rooted in generative AI. Principal sought to develop natural language processing (NLP) and question-answering capabilities to accurately query and summarize this unstructured data at scale.

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Implement RAG while meeting data residency requirements using AWS hybrid and edge services

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In this post, we show how to extend Amazon Bedrock Agents to hybrid and edge services such as AWS Outposts and AWS Local Zones to build distributed Retrieval Augmented Generation (RAG) applications with on-premises data for improved model outcomes.

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