Machine learning & AI
Topics
- Aggregate data in Amazon DynamoDB for ML forecasting in Athena
- Associate an AWS CodeCommit repository in one AWS account with SageMaker Studio in another account
- Automate Amazon Lookout for Vision training and deployment for anomaly detection
- Automatically extract content from PDF files using Amazon Textract
- Build an MLOps workflow by using Amazon SageMaker and Azure DevOps
- Create a custom Docker container image for SageMaker and use it for model training in AWS Step Functions
- Deploy preprocessing logic into an ML model in a single endpoint using an inference pipeline in Amazon SageMaker
- 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
- Train and deploy a custom GPU-supported ML model on Amazon SageMaker
- Use SageMaker Processing for distributed feature engineering of terabyte-scale ML datasets
- Visualize AI/ML model results using Flask and AWS Elastic Beanstalk
- More patterns
