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Build a multilingual automatic translation pipeline with Amazon Translate Active Custom Translation

AWS Machine Learning Blog

In the following sections, we demonstrate how to build each translation pipeline using Amazon Translate with ACT, along with Amazon SageMaker and Amazon Simple Storage Service (Amazon S3). The following example is extracted from D2L-en book and D2L-zh book. The following screenshot shows an example of a CSV input file.

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Announcing the updated Microsoft SharePoint connector (V2.0) for Amazon Kendra

AWS Machine Learning Blog

In the following sections, we go through the steps to create an index, add the SharePoint connector, and test the solution. An AWS account with privileges to create AWS Identity and Access Management (IAM) roles and policies. Choose English (en) for Default language. Under SharePoint Connector V2.0 , choose Add connector.

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Simplify continuous learning of Amazon Comprehend custom models using Comprehend flywheel

AWS Machine Learning Blog

Prerequisites To complete this walkthrough, you need an AWS account and access to create resources in AWS Identity and Access Management (IAM), Amazon S3 and Amazon Comprehend within the account. You can easily create another endpoint whenever you need it from the Endpoints section. The data can be accessed from AWS Open Data Registry.

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Streamline diarization using AI as an assistive technology: ZOO Digital’s story

AWS Machine Learning Blog

Typical localization workflows require manual speaker diarization, wherein an audio stream is segmented based on the identity of the speaker. In the following sections, we delve into the details of deploying the WhisperX model on SageMaker, and evaluate the diarization performance. in a code subdirectory.

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Natural Language Processing with R

Heartbeat

The first section of this article will look at the various languages that can be used for NLP, and the second section will focus on five NLP packages available in the R language. Each element in the text has its own identity, which is referred to as an element id. Print the tokens print(tokens) 3.

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Manage your Amazon Lex bot via AWS CloudFormation templates

AWS Machine Learning Blog

See the following code: BotLocales: - LocaleId: "en_US" Description: "en US locale" NluConfidenceThreshold: 0.40 You can do so in the BotAliasLocalSettings section. Additionally, we explore topics such as version control, aliases, integrating AWS Lambda functions, creating conditional branches, and enabling logging.

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Advanced RAG patterns on Amazon SageMaker

AWS Machine Learning Blog

Solution overview In this post, we demonstrate the use of Mixtral-8x7B Instruct text generation combined with the BGE Large En embedding model to efficiently construct a RAG QnA system on an Amazon SageMaker notebook using the parent document retriever tool and contextual compression technique. We use an ml.t3.medium

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