Remove solutions construction-and-engineering
article thumbnail

Improve LLM performance with human and AI feedback on Amazon SageMaker for Amazon Engineering

AWS Machine Learning

The Amazon EU Design and Construction (Amazon D&C) team is the engineering team designing and constructing Amazon warehouses. The Amazon D&C team implemented the solution in a pilot for Amazon engineers and collected user feedback.

article thumbnail

Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention

AWS Machine Learning

Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. In this post, we discuss how the AWS AI/ML team collaborated with the Merck Human Health IT MLOps team to build a solution that uses an automated workflow for ML model approval and promotion with human intervention in the middle.

APIs 101
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Personalize your generative AI applications with Amazon SageMaker Feature Store

AWS Machine Learning

Large language models (LLMs) are revolutionizing fields like search engines, natural language processing (NLP), healthcare, robotics, and code generation. Another essential component is an orchestration tool suitable for prompt engineering and managing different type of subtasks.

article thumbnail

Set up Amazon SageMaker Studio with Jupyter Lab 3 using the AWS CDK

AWS Machine Learning

AWS CDK constructs are the building blocks of AWS CDK applications, representing the blueprint to define cloud architectures. This development approach can be used in combination with other common software engineering best practices such as automated code deployments, tests, and CI/CD pipelines. Studio construct file.

article thumbnail

Getir end-to-end workforce management: Amazon Forecast and AWS Step Functions

AWS Machine Learning

In this post, we describe how we reduced the modelling time by 70% by doing the feature engineering and modelling using Amazon Forecast. This solution also led to an 90% improvement in prediction accuracy across Turkey and several European countries. Getir is the pioneer of ultrafast grocery delivery.

article thumbnail

Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning

Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs to ML models used during training and inference. Features are used repeatedly by multiple teams, and feature quality is critical to ensure a highly accurate model.

article thumbnail

Improve your Stable Diffusion prompts with Retrieval Augmented Generation

AWS Machine Learning

In November 2022, we announced that AWS customers can generate images from text with Stable Diffusion models in Amazon SageMaker JumpStart , a machine learning (ML) hub offering models, algorithms, and solutions. Stable Diffusion is a text-to-image model that empowers you to create high-quality images within seconds.