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	<title>Amazon SageMaker Studio &#8211; Noise</title>
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		<title>Optimize efficiency with language analyzers using scalable multilingual search in Amazon OpenSearch Service</title>
		<link>https://noise.getoto.net/2025/10/03/optimize-efficiency-with-language-analyzers-using-scalable-multilingual-search-in-amazon-opensearch-service/</link>
		
		<dc:creator><![CDATA[Sunil Ramachandra]]></dc:creator>
		<pubDate>Thu, 02 Oct 2025 22:13:45 +0000</pubDate>
				<category><![CDATA[Amazon OpenSearch Service]]></category>
		<category><![CDATA[Amazon SageMaker Studio]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Organizations manage content across multiple languages as they expand globally. Ecommerce platforms, customer support systems, and knowledge bases require efficient multilingual search capabilities to serve diverse user bases effectively. This unified search approach helps multinational organizations maintain centralized content repositories while making sure users, regardless of their preferred language, can effectively find and access relevant […]]]></description>
		
		
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		<title>Introducing Llama 3.2 models from Meta in Amazon Bedrock: A new generation of multimodal vision and lightweight models</title>
		<link>https://noise.getoto.net/2024/09/25/introducing-llama-3-2-models-from-meta-in-amazon-bedrock-a-new-generation-of-multimodal-vision-and-lightweight-models/</link>
		
		<dc:creator><![CDATA[Danilo Poccia]]></dc:creator>
		<pubDate>Wed, 25 Sep 2024 18:18:52 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon SageMaker JumpStart]]></category>
		<category><![CDATA[Amazon SageMaker Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Featured]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
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					<description><![CDATA[Pushing the boundaries of generative AI, Meta unveils Llama 3.2, a groundbreaking language model family featuring enhanced capabilities, broader applicability, and multimodal image support, now available in Amazon Bedrock.]]></description>
		
		
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		<item>
		<title>Introducing Amazon Q Developer in SageMaker Studio to streamline ML workflows</title>
		<link>https://noise.getoto.net/2024/07/10/introducing-amazon-q-developer-in-sagemaker-studio-to-streamline-ml-workflows/</link>
		
		<dc:creator><![CDATA[Esra Kayabali]]></dc:creator>
		<pubDate>Wed, 10 Jul 2024 15:24:20 +0000</pubDate>
				<category><![CDATA[Amazon Q]]></category>
		<category><![CDATA[Amazon SageMaker Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS Summit New York]]></category>
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					<description><![CDATA[Streamline your ML workflows with this generative AI assistant providing tailored guidance, code generation, and error troubleshooting, to build, train, and deploy models efficiently.]]></description>
		
		
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		<item>
		<title>AWS Weekly Roundup: Anthropic’s Claude 3 Opus in Amazon Bedrock, Meta Llama 3 in Amazon SageMaker JumpStart, and more (April 22, 2024)</title>
		<link>https://noise.getoto.net/2024/04/22/aws-weekly-roundup-anthropics-claude-3-opus-in-amazon-bedrock-meta-llama-3-in-amazon-sagemaker-jumpstart-and-more-april-22-2024/</link>
		
		<dc:creator><![CDATA[Esra Kayabali]]></dc:creator>
		<pubDate>Mon, 22 Apr 2024 17:32:54 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon Elastic Kubernetes Service]]></category>
		<category><![CDATA[Amazon SageMaker JumpStart]]></category>
		<category><![CDATA[Amazon SageMaker Studio]]></category>
		<category><![CDATA[AWS Key Management Service*]]></category>
		<category><![CDATA[news]]></category>
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					<description><![CDATA[AWS Summits continue to rock the world, with events taking place in various locations around the globe. AWS Summit London (April 24) is the last one in April, and there are nine more in May, including AWS Summit Berlin (May 15–16), AWS Summit Los Angeles (May 22), and AWS Summit Dubai (May 29). Join us […]]]></description>
		
		
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		<title>Generate AI powered insights for Amazon Security Lake using Amazon SageMaker Studio and Amazon Bedrock</title>
		<link>https://noise.getoto.net/2024/01/17/generate-ai-powered-insights-for-amazon-security-lake-using-amazon-sagemaker-studio-and-amazon-bedrock/</link>
		
		<dc:creator><![CDATA[Jonathan Nguyen]]></dc:creator>
		<pubDate>Tue, 16 Jan 2024 22:00:29 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon SageMaker Studio]]></category>
		<category><![CDATA[Amazon Security Lake]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<category><![CDATA[Expert (400)]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[SageMaker]]></category>
		<category><![CDATA[Security Blog]]></category>
		<category><![CDATA[Security, Identity & Compliance]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In part 1, we discussed how to use Amazon SageMaker Studio to analyze time-series data in Amazon Security Lake to identify critical areas and prioritize efforts to help increase your security posture. Security Lake provides additional visibility into your environment by consolidating and normalizing security data from both AWS and non-AWS sources. Security teams can […]]]></description>
		
		
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		<title>Amazon SageMaker Studio adds web-based interface, Code Editor, flexible workspaces, and streamlines user onboarding</title>
		<link>https://noise.getoto.net/2023/11/30/amazon-sagemaker-studio-adds-web-based-interface-code-editor-flexible-workspaces-and-streamlines-user-onboarding/</link>
		
		<dc:creator><![CDATA[Antje Barth]]></dc:creator>
		<pubDate>Thu, 30 Nov 2023 18:18:30 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
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					<description><![CDATA[Today, we are announcing an improved Amazon SageMaker Studio experience! The new SageMaker Studio web-based interface loads faster and provides consistent access to your preferred integrated development environment (IDE) and SageMaker resources and tooling, irrespective of your IDE choice. In addition to JupyterLab and RStudio, SageMaker Studio now includes a fully managed Code Editor based […]]]></description>
		
		
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		<item>
		<title>Package and deploy models faster with new tools and guided workflows in Amazon SageMaker</title>
		<link>https://noise.getoto.net/2023/11/29/package-and-deploy-models-faster-with-new-tools-and-guided-workflows-in-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Antje Barth]]></dc:creator>
		<pubDate>Wed, 29 Nov 2023 19:14:45 +0000</pubDate>
				<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon SageMaker Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=103036531aa5f1971011d0a48e431fa3</guid>

					<description><![CDATA[I’m happy to share that Amazon SageMaker now comes with an improved model deployment experience to help you deploy traditional machine learning (ML) models and foundation models (FMs) faster. As a data scientist or ML practitioner, you can now use the new ModelBuilder class in the SageMaker Python SDK to package models, perform local inference […]]]></description>
		
		
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		<item>
		<title>Implement fine-grained access control in Amazon SageMaker Studio and Amazon EMR using Apache Ranger and Microsoft Active Directory</title>
		<link>https://noise.getoto.net/2023/11/08/implement-fine-grained-access-control-in-amazon-sagemaker-studio-and-amazon-emr-using-apache-ranger-and-microsoft-active-directory/</link>
		
		<dc:creator><![CDATA[Rahul Sarda]]></dc:creator>
		<pubDate>Wed, 08 Nov 2023 17:52:47 +0000</pubDate>
				<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon SageMaker Studio]]></category>
		<category><![CDATA[Best practices]]></category>
		<category><![CDATA[Expert (400)]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=4ddee9bce4fe6ced3deb2d1d1ee72f55</guid>

					<description><![CDATA[In this post, we show how you can authenticate into SageMaker Studio using an existing Active Directory (AD), with authorized access to both Amazon S3 and Hive cataloged data using AD entitlements via Apache Ranger integration and AWS IAM Identity Center (successor to AWS Single Sign-On). With this solution, you can manage access to multiple SageMaker environments and SageMaker Studio notebooks using a single set of credentials. Subsequently, Apache Spark jobs created from SageMaker Studio notebooks will access only the data and resources permitted by Apache Ranger policies attached to the AD credentials, inclusive of table and column-level access.]]></description>
		
		
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		<item>
		<title>Create, train, and deploy Amazon Redshift ML model integrating features from Amazon SageMaker Feature Store</title>
		<link>https://noise.getoto.net/2023/10/26/create-train-and-deploy-amazon-redshift-ml-model-integrating-features-from-amazon-sagemaker-feature-store/</link>
		
		<dc:creator><![CDATA[Anirban Sinha]]></dc:creator>
		<pubDate>Thu, 26 Oct 2023 17:19:48 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon Redshift Spectrum]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon SageMaker Studio]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=7c4176a8627338bad6a28c9aab307459</guid>

					<description><![CDATA[Amazon Redshift is a fast, petabyte-scale, cloud data warehouse that tens of thousands of customers rely on to power their analytics workloads. Data analysts and database developers want to use this data to train machine learning (ML) models, which can then be used to generate insights on new data for use cases such as forecasting […]]]></description>
		
		
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