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 Overview of solution.

article thumbnail

Facebook’s Conversion API – what marketers need to know

Infinity

So, in autumn 2021, when Facebook partnered up with Amazon and launched the Conversion API Gateway, it was a very exciting day for Facebook advertisers. When talking Facebook and data, you’re likely to come across two key models – the Conversion API Gateway and the Facebook Pixel, but what’s the difference?

APIs 52
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

Customize Amazon Textract with business-specific documents using Custom Queries

AWS Machine Learning

You can use the adapter for inference by passing the adapter identifier as an additional parameter to the Analyze Document Queries API request. Adapters can be created via the console or programmatically via the API. What is the account#? What is the account name/payer/drawer name? MICR line format). Who is the payee?

APIs 107
article thumbnail

Build a cross-account MLOps workflow using the Amazon SageMaker model registry

AWS Machine Learning

When designing production CI/CD pipelines, AWS recommends leveraging multiple accounts to isolate resources, contain security threats and simplify billing-and data science pipelines are no different. Some things to note in the preceding architecture: Accounts follow a principle of least privilege to follow security best practices.

article thumbnail

Live Meeting Assistant with Amazon Transcribe, Amazon Bedrock, and Knowledge Bases for Amazon Bedrock

AWS Machine Learning

It’s straightforward to deploy in your AWS account. Prerequisites You need to have an AWS account and an AWS Identity and Access Management (IAM) role and user with permissions to create and manage the necessary resources and components for this application. Everything you need is provided as open source in our GitHub repo.

APIs 83
article thumbnail

How Yara is using MLOps features of Amazon SageMaker to scale energy optimization across their ammonia plants

AWS Machine Learning

Their production segment is therefore an integral building block for delivering on their mission—with a clearly stated ambition to become world-leading on metrics such as safety, environmental footprint, quality, and production costs. Yara has built APIs using Amazon API Gateway to expose the sensor data to applications such as ELC.

APIs 96
article thumbnail

Automate mortgage document fraud detection using an ML model and business-defined rules with Amazon Fraud Detector: Part 3

AWS Machine Learning

Deploy the API to make predictions. Prerequisites The following are prerequisite steps for this solution: Sign up for an AWS account. Set up permissions that allows your AWS account to access Amazon Fraud Detector. Review model performance. Deploy the model. Create a detector. Add rules to interpret model scores. Choose Next.

APIs 113