AI & machine learning

Topics

Associate an AWS CodeCommit repository in one AWS account with Amazon SageMaker AI Studio Classic in another account
Automatically extract content from PDF files using Amazon Textract
Build a cold start forecasting model by using DeepAR for time series in Amazon SageMaker AI Studio Lab
Build an MLOps workflow by using Amazon SageMaker AI and Azure DevOps
Configure model invocation logging in Amazon Bedrock by using AWS CloudFormation
Create a custom Docker container image for SageMaker and use it for model training in AWS Step Functions
Use Amazon Bedrock agents to automate creation of access entry controls in Amazon EKS through text-based prompts
Deploy a RAG use case on AWS by using Terraform and Amazon Bedrock
Deploy preprocessing logic into an ML model in a single endpoint using an inference pipeline in Amazon SageMaker
Deploy real-time coding security validation by using an MCP server with Kiro and other coding assistants
Develop advanced generative AI chat-based assistants by using RAG and ReAct prompting
Develop a fully automated chat-based assistant by using Amazon Bedrock agents and knowledge bases
Document institutional knowledge from voice inputs by using Amazon Bedrock and Amazon Transcribe
Generate personalized and re-ranked recommendations using Amazon Personalize
Streamline machine learning workflows from local development to scalable experiments by using SageMaker AI and Hydra
Translate natural language into query DSL for OpenSearch and Elasticsearch queries
Use Amazon Q Developer as a coding assistant to increase your productivity
Use SageMaker Processing for distributed feature engineering of terabyte-scale ML datasets
Visualize AI/ML model results using Flask and AWS Elastic Beanstalk
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More patterns

Associate an AWS CodeCommit repository with Amazon SageMaker AI Studio Classic across accounts