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Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

AWS Machine Learning

By using the Livy REST APIs , SageMaker Studio users can also extend their interactive analytics workflows beyond just notebook-based scenarios, enabling a more comprehensive and streamlined data science experience within the Amazon SageMaker ecosystem. elasticmapreduce", "arn:aws:s3:::*.elasticmapreduce/*"

Big data 115
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Build a multilingual automatic translation pipeline with Amazon Translate Active Custom Translation

AWS Machine Learning

We demonstrate how to use the AWS Management Console and Amazon Translate public API to deliver automatic machine batch translation, and analyze the translations between two language pairs: English and Chinese, and English and Spanish. In this post, we present a solution that D2L.ai

APIs 93
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Dive deep into vector data stores using Amazon Bedrock Knowledge Bases

AWS Machine Learning

Amazon Bedrock makes it straightforward to adopt any of these choices by providing a common set of APIs, industry-leading embedding models, security, governance, and observability. In this post, we discuss use cases, features, and steps to set up and retrieve information using these vector databases.

APIs 102
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Fine-tune Anthropic’s Claude 3 Haiku in Amazon Bedrock to boost model accuracy and quality

AWS Machine Learning

Run the fine-tuning job using the Amazon Bedrock API Make sure to request access to the preview of Anthropic Claude 3 Haiku fine-tuning in Amazon Bedrock, as discussed in the prerequisites. Prerequisites To use this feature, make sure you have satisfied the following requirements: An active AWS account.

APIs 133
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Use Amazon SageMaker Studio with a custom file system in Amazon EFS

AWS Machine Learning

You should have an AWS CloudTrail log file that logs the SageMaker API CreateUserProfile. If the access to AWS services in the selected VPC is restricted using AWS PrivateLink , make sure the Lambda security group can connect to the interface VPC endpoints for SageMaker (API), Amazon EFS, and Amazon Elastic Compute Cloud (Amazon EC2).

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Bring legacy machine learning code into Amazon SageMaker using AWS Step Functions

AWS Machine Learning

The best practice for migration is to refactor these legacy codes using the Amazon SageMaker API or the SageMaker Python SDK. Step Functions is a serverless workflow service that can control SageMaker APIs directly through the use of the Amazon States Language. We do so using AWS SDK for Python (Boto3) CreateProcessingJob API calls.

Scripts 137
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Brevo (Formely Sendinblue): Features and Services

JivoChat

Brevo Overview In 2012, Sendinblue was launched as a newsletter service, along the years the company has expanded its service considerably, which led to the name change, as well, Brevo. Use the analytics tools to track how each email performs, and check out key performance indicators (KPIs), like open, click-through, and bounce rates.

APIs 75