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Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

AWS Machine Learning Blog

Create a KMS key in the dev account and give access to the prod account Complete the following steps to create a KMS key in the dev account: On the AWS KMS console, choose Customer managed keys in the navigation pane. Choose Create key. For Key type , select Symmetric.

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Fine-tune multimodal models for vision and text use cases on Amazon SageMaker JumpStart

AWS Machine Learning Blog

In the metadata.jsonl file, each example is a dictionary that contains three keys named file_name , prompt , and completion. prompt defines the text input prompt and completion defines the text completion corresponding to the input prompt. jpg", "prompt": "what is the contact person name mentioned in letter?", "completion": "P.

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Making Sense of the Mess: LLMs Role in Unstructured Data Extraction

Unite.AI

Like RNNs, LSTMs excel in extracting key-value pairs from sentences, However, they face similar challenges with table-like structures, demanding a strategic consideration of sequence and positional elements. GPUs were first used for deep learning in 2012 to develop the famous AlexNet CNN model.

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AI-powered code suggestions and security scans in Amazon SageMaker notebooks using Amazon CodeWhisperer and Amazon CodeGuru

AWS Machine Learning Blog

To get started, complete the following steps: On the File menu, choose New and Terminal. Use CodeWhisperer in Studio After we complete the installation steps, we can use CodeWhisperer by opening a new notebook or Python file. In this section, we look at the steps involved. For our example we will open a sample Notebook.

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16 Companies Leading the Way in AI and Data Science

ODSC - Open Data Science

Going from Data to Insights LexisNexis At HPCC Systems® from LexisNexis® Risk Solutions you’ll find “a consistent data-centric programming language, two processing platforms, and a single, complete end-to-end architecture for efficient processing.” These tools are designed to help companies derive insights from big data.

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

AWS Machine Learning Blog

When the job is complete, the parallel data status shows as Active and is ready to use. When the job status changes into Completed , we can find the translated documents in Chinese (D2L-zh) in the S3 bucket output folder. We can check the training job progress on the Amazon Translate console.

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Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

Flipboard

Deploy the CloudFormation template Complete the following steps to deploy the CloudFormation template: Save the CloudFormation template sm-redshift-demo-vpc-cfn-v1.yaml Launch SageMaker Studio Complete the following steps to launch your SageMaker Studio domain: On the SageMaker console, choose Domains in the navigation pane.

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