Remove Accountability Remove Engineering Remove Metrics
article thumbnail

Transitioning off Amazon Lookout for Metrics 

AWS Machine Learning

Amazon Lookout for Metrics is a fully managed service that uses machine learning (ML) to detect anomalies in virtually any time-series business or operational metrics—such as revenue performance, purchase transactions, and customer acquisition and retention rates—with no ML experience required.

Metrics 88
article thumbnail

Build a reverse image search engine with Amazon Titan Multimodal Embeddings in Amazon Bedrock and AWS managed services

AWS Machine Learning

A reverse image search engine enables users to upload an image to find related information instead of using text-based queries. Solution overview The solution outlines how to build a reverse image search engine to retrieve similar images based on input image queries. Engine : Select nmslib. Distance metric : Select Euclidean.

Insiders

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

20 Call Center Pros Share the Most Undervalued Call Center Metrics and How To Better Leverage Them

Callminer

From essentials like average handle time to broader metrics such as call center service levels , there are dozens of metrics that call center leaders and QA teams must stay on top of, and they all provide visibility into some aspect of performance. Kaye Chapman @kayejchapman. First contact resolution (FCR) measures might be…”.

article thumbnail

How Vericast optimized feature engineering using Amazon SageMaker Processing

AWS Machine Learning

One aspect of this data preparation is feature engineering. Feature engineering refers to the process where relevant variables are identified, selected, and manipulated to transform the raw data into more useful and usable forms for use with the ML algorithm used to train a model and perform inference against it.

article thumbnail

Build a contextual text and image search engine for product recommendations using Amazon Bedrock and Amazon OpenSearch Serverless

AWS Machine Learning

Search engines and recommendation systems powered by generative AI can improve the product search experience exponentially by understanding natural language queries and returning more accurate results. Amazon OpenSearch Service now supports the cosine similarity metric for k-NN indexes.

article thumbnail

Prevent account takeover at login with the new Account Takeover Insights model in Amazon Fraud Detector

AWS Machine Learning

So much exposure naturally brings added risks like account takeover (ATO). Each year, bad actors compromise billions of accounts through stolen credentials, phishing, social engineering, and multiple forms of ATO. To put it into perspective: account takeover fraud increased by 90% to an estimated $11.4

article thumbnail

Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM) , making it easier to securely share and discover machine learning (ML) models across your AWS accounts. Mitigation strategies : Implementing measures to minimize or eliminate risks.