Anomaly Detection

Databricks Machine Learning

Scaling AutoML-Driven Anomaly Detection with Luminaire

Zillow has built an orchestration framework around Luminaire, our open-source python library for hands-off time-series Anomaly Detection. Luminaire provides a suite of models and built-in AutoML capabilities which they process with Spark for distributed training and scoring of thousands of metrics. In this talk, learn the architecture of this framework and performance of the Luminaire […]

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Azure Databricks

Anomaly Detection on Streaming Data Using Azure Databricks

In our previous episodes of the AI Show, we’ve learned all about the Azure Anomaly detector, how to bring the service on premises, and some awesome tips and tricks for getting the service to work well for you. In this episode of the AI Show, Qun Ying shows us how to build an end-to-end solution […]

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AI Azure

Bring Anomaly Detector On-Premise with Containers

In this episode, learn how the Anomaly Detection service comes to your on-premises systems via containers. By deploying the same API service close to your data in containers, now you don’t have to worry about situations when you have to keep the data on-premises to follow regulation, or to deal with network latency, or just […]

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AI Azure

Introducing Azure Anomaly Detector

In this episode of the AI Show, get a look at a simple way to detect anomalies that can occur in your data. Knowing when something goes off the rails is incredibly important and now easily done with a simple API call. Azure Anomaly Detector Related Links Check out the overview of the API service […]

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AI Data Science

Anomaly Detection Transform in ML.NET

Jon Wood has just posted this excellent video (and related code) on using an ML.NET transform to detect anomalies in time series data.

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Azure IoT Machine Learning

Real-Time ML Based Anomaly Detection In Azure Stream Analytics

Azure Stream Analytics is a PaaS cloud offering on Microsoft Azure to help customers analyze IoT telemetry data in real-time. Stream Analytics now has embedded ML models for Anomaly Detection, which can be invoked with simple function calls. Learn how you can leverage this powerful feature set for your scenarios. Learn more : https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-machine-learning-anomaly-detection Create […]

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Azure Anomaly Detector service spots business data deviations
Azure Machine Learning Microsoft

Azure Anomaly Detector service spots business data deviations

There’s a new Cognitive Service in town and it detects anomalies. From the article in TechTarget. The Azure Anomaly Detector service, now in preview, is an addition to Azure Cognitive Services. It takes in customers’ time-series data — information collected at and stamped with specific points in time — and applies the most efficient algorithm […]

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TensorFlow

Deploying a Fraud Detection Microservice using TensorFlow, PySpark, and Cortex

The most popular dataset on Kaggle is  Credit Card Fraud Detection. It’s an easy to understand problem space and impacts just about everyone. Fraud detection is a practical application that many businesses care about.  There’s a also something intrinsically cool about stopping crime with AI. Here’s an interesting article on how to implement a fraud […]

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Deep Learning Machine Learning

Fraud Detection Using a Neural Autoencoder

Fraud detection, a common use of AI, belongs to a more general class of problems — anomaly detection. An anomaly is a generic, not domain-specific, concept. It refers to any exceptional or unexpected event in the data: a mechanical piece failure, an arrhythmic heartbeat, or a fraudulent transaction. Basically, identifying a fraud means identifying an […]

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