Remove 2014 Remove Algorithm Remove AWS
article thumbnail

Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 2

AWS Machine Learning Blog

To mitigate these challenges, we propose a federated learning (FL) framework, based on open-source FedML on AWS, which enables analyzing sensitive HCLS data. In this two-part series, we demonstrate how you can deploy a cloud-based FL framework on AWS. In the first post , we described FL concepts and the FedML framework.

AWS 86
article thumbnail

Keeping an eye on your cattle using AI technology

AWS Machine Learning Blog

At Amazon Web Services (AWS) , not only are we passionate about providing customers with a variety of comprehensive technical solutions, but we’re also keen on deeply understanding our customers’ business processes. This method is called working backwards at AWS. Project background Milk is a nutritious beverage.

AWS 123
professionals

Sign Up for our Newsletter

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

Trending Sources

article thumbnail

Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

AWS Machine Learning Blog

This is a joint blog with AWS and Philips. Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to improve patient care.

AWS 114
article thumbnail

How Veritone uses Amazon Bedrock, Amazon Rekognition, Amazon Transcribe, and information retrieval to update their video search pipeline

AWS Machine Learning Blog

Founded in 2014, Veritone empowers people with AI-powered software and solutions for various applications, including media processing, analytics, advertising, and more. The primary focus is building a robust text search that goes beyond traditional word-matching algorithms as well as an interface for comparing search algorithms.

AWS 128
article thumbnail

Prioritizing employee well-being: An innovative approach with generative AI and Amazon SageMaker Canvas

AWS Machine Learning Blog

based single sign-on (SSO) methods, such as AWS IAM Identity Center. To learn more, see Secure access to Amazon SageMaker Studio with AWS SSO and a SAML application. For more information, see AWS managed policy: AmazonSageMakerCanvasAIServicesAccess. For more information, see Training modes and algorithm support.

AWS 117
article thumbnail

Explain text classification model predictions using Amazon SageMaker Clarify

AWS Machine Learning Blog

Apart from supporting explanations for tabular data, Clarify also supports explainability for both computer vision (CV) and natural language processing (NLP) using the same SHAP algorithm. Specifically, we show how you can explain the predictions of a text classification model that has been trained using the SageMaker BlazingText algorithm.

article thumbnail

Personalize your generative AI applications with Amazon SageMaker Feature Store

AWS Machine Learning Blog

To simplify, you can build a regression algorithm using a user’s previous ratings across different categories to infer their overall preferences. This can be done with algorithms like XGBoost. Next, we recommend “Interstellar” (2014), a thought-provoking and visually stunning film that delves into the mysteries of time and space.

AI 131