Using Amazon SageMaker inference pipelines with multi-model endpoints

Businesses are increasingly deploying multiple machine learning (ML) models to serve precise and accurate predictions to their consumers. Consider a media company that wants to provide recommendations to its subscribers. The company may want to employ different custom models for recommending different categories of products—such as movies, books, music, and Read more…

CFTC officials publish new crypto advisory for futures commission merchants

The Commodity Futures Trading Commission (CFTC)’s Division of Swap Dealer and Intermediary Oversight published new guidance late Wednesday “regarding the holding of virtual currency in segregated accounts” by futures commission merchants, or FCMs. “The advisory provides guidance to FCMs on how to hold and report certain deposited virtual currency from customers Read more…

Time series forecasting using unstructured data with Amazon Forecast and the Amazon SageMaker Neural Topic Model

As the volume of unstructured data such as text and voice continues to grow, businesses are increasingly looking for ways to incorporate this data into their time series predictive modeling workflows. One example use case is transcribing calls from call centers to forecast call handle times and improve call volume Read more…

Performing batch fraud predictions using Amazon Fraud Detector, Amazon S3, and AWS Lambda

Amazon Fraud Detector is a fully managed service that makes it easy to identify potentially fraudulent online activities, such as the creation of fake accounts or online payment fraud. Unlike general-purpose machine learning (ML) packages, Amazon Fraud Detector is designed specifically to detect fraud. Amazon Fraud Detector combines your data, Read more…

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