Remove meet-anomaly
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Amazing Business Radio: Scot Pickerill

ShepHyken

Document them, and determine if they are an anomaly or brewing bigger issues. Plus, Scot shares how buying behaviors have changed in the last couple of years and how businesses can design their strategy to meet customer expectations. Make a note of the issues that happen often. Treat your customers as partners.

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Detect anomalies in manufacturing data using Amazon SageMaker Canvas

AWS Machine Learning

In this post, we show you how to use SageMaker Canvas to curate and select the right features in your data, and then train a prediction model for anomaly detection, using the no-code functionality of SageMaker Canvas for model tuning. For this post, we demonstrate how these capabilities can also help detect complex abnormal data points.

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How Prodege saved $1.5 million in annual human review costs using low-code computer vision AI

AWS Machine Learning

They didn’t have an automated way to visually inspect the receipts for anomalies before issuing rebates. Because the volume of receipts was in the tens of thousands per week, the manual process of identifying anomalies wasn’t scalable. The challenge: Detecting anomalies in receipts quickly and accurately at scale.

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Real-Time Adaptive Intraday Management Saves the Day

DMG Consulting

Anomalies can be caused by any number of unforeseen scenarios including a much higher than planned response rate to a marketing campaign or the surf being up along the coast, increasing the shrinkage rate.

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Use machine learning to detect anomalies and predict downtime with Amazon Timestream and Amazon Lookout for Equipment

AWS Machine Learning

Still, challenges remain for teams of all sizes to quickly, and with little effort, demonstrate the value of ML-based anomaly detection in order to persuade management and finance owners to allocate the budget required to implement these new technologies. You need access to an AWS account to set up the environment for anomaly detection.

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

AWS Machine Learning

As you start to prepare your login data, you must meet the following requirements: Provide at least 1,500 entities (individual user accounts), each with at least two associated login events. ATI is an anomaly detection model rather than a classification model; therefore, the evaluation metrics differ from classification models.

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How to Use Data Analytics to Improve High Roller Casino Customer Service

CSM Magazine

These VIP patrons demand a personalized and seamless experience, and casinos can meet these expectations by leveraging data analytics. This enables them to tailor promotions, offers, and services to meet the specific needs and desires of individual high rollers. Many casinos go out of their way to make their high rollers happy.