Remove APIs Remove Entertainment Remove Personalization Remove Scripts
article thumbnail

Drive hyper-personalized customer experiences with Amazon Personalize and generative AI

AWS Machine Learning

Today, we are excited to announce three launches that will help you enhance personalized customer experiences using Amazon Personalize and generative AI. Amazon Personalize is a fully managed machine learning (ML) service that makes it easy for developers to deliver personalized experiences to their users.

article thumbnail

Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning

The Retrieve and RetrieveAndGenerate APIs allow your applications to directly query the index using a unified and standard syntax without having to learn separate APIs for each different vector database, reducing the need to write custom index queries against your vector store.

APIs 110
Insiders

Sign Up for our Newsletter

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

article thumbnail

Identify key insights from text documents through fine-tuning and HPO with Amazon SageMaker JumpStart

AWS Machine Learning

Personalized recommendations. This notebook demonstrates how to use the JumpStart API for text classification. To run inference on this model, we first need to download the inference container ( deploy_image_uri ), inference script ( deploy_source_uri ), and pre-trained model ( base_model_uri ). Credit rating prediction.

Scripts 71
article thumbnail

How Amp on Amazon used data to increase customer engagement, Part 1: Building a data analytics platform

AWS Machine Learning

Amp wanted a scalable data and analytics platform to enable easy access to data and perform machine leaning (ML) experiments for live audio transcription, content moderation, feature engineering, and a personal show recommendation service, and to inspect or measure business KPIs and metrics. This post is the first in a two-part series.

article thumbnail

FMOps/LLMOps: Operationalize generative AI and differences with MLOps

AWS Machine Learning

Note that multiple personas can be covered by the same person depending on the scaling and MLOps maturity of the business. Example use cases are clothing design generation or imaginary personalized images. Some models may be trained on diverse text datasets like internet data, coding scripts, instructions, or human feedback.

article thumbnail

Semantic image search for articles using Amazon Rekognition, Amazon SageMaker foundation models, and Amazon OpenSearch Service

AWS Machine Learning

Amazon Rekognition makes it easy to add image analysis capability to your applications without any machine learning (ML) expertise and comes with various APIs to fulfil use cases such as object detection, content moderation, face detection and analysis, and text and celebrity recognition, which we use in this example.

APIs 93
article thumbnail

Easily build semantic image search using Amazon Titan

AWS Machine Learning

Amazon Rekognition automatically recognizes tens of thousands of well-known personalities in images and videos using ML. The function then searches the OpenSearch Service image index for images matching the celebrity name and the k-nearest neighbors for the vector using cosine similarity using Exact k-NN with scoring script.

Scripts 91