Analytics APIs How To 
AWS Machine Learning
NOVEMBER 7, 2024
It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. API Gateway is serverless and hence automatically scales with traffic. API Gateway also provides a WebSocket API. Incoming requests to the gateway go through this point.
AWS Machine Learning
OCTOBER 29, 2024
Furthermore, these notes are usually personal and not stored in a central location, which is a lost opportunity for businesses to learn what does and doesn’t work, as well as how to improve their sales, purchasing, and communication processes. It also supports audio files so you have flexibility around the type of call recordings you use.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
AWS Machine Learning
DECEMBER 4, 2024
SageMaker Unified Studio setup SageMaker Unified Studio is a browser-based web application where you can use all your data and tools for analytics and AI. This will provision the backend infrastructure and services that the sales analytics application will rely on. You’ll use this file when setting up your function to query sales data.
AWS Machine Learning
OCTOBER 31, 2024
Refer to How Amazon Q Business connector crawls Gmail ACLs for more information. Solution overview In the following sections, we demonstrate how to set up the Gmail connector for Amazon Q Business. Then we provide examples of how to use the AI-powered chat interface to gain insights from the connected data source. Choose Enable.
AWS Machine Learning
APRIL 10, 2025
You can get started without any prior machine learning (ML) experience, and Amazon Personalize allows you to use APIs to build sophisticated personalization capabilities. In this post, we demonstrate how to use Amazon Personalize and Amazon Bedrock to generate personalized outreach emails for individual users using a video-on-demand use case.
AWS Machine Learning
JANUARY 28, 2025
In this post, we show how to use FMEval and Amazon SageMaker to programmatically evaluate LLMs. SageMaker is a data, analytics, and AI/ML platform, which we will use in conjunction with FMEval to streamline the evaluation process. We specifically focus on SageMaker with MLflow. This allows you to keep track of your ML experiments.
AWS Machine Learning
FEBRUARY 21, 2025
Solution overview Our solution implements a verified semantic cache using the Amazon Bedrock Knowledge Bases Retrieve API to reduce hallucinations in LLM responses while simultaneously improving latency and reducing costs. The function checks the semantic cache (Amazon Bedrock Knowledge Bases) using the Retrieve API.
Expert insights. Personalized for you.
113 
Let's personalize your content