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Machine Learning with MATLAB and Amazon SageMaker

Flipboard

In recent years, MathWorks has brought many product offerings into the cloud, especially on Amazon Web Services (AWS). Because we have a model of the system and faults are rare in operation, we can take advantage of simulated data to train our algorithm. Here is a quick guide on how to run MATLAB on AWS.  Either Ubuntu or Linux.

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Transitioning off Amazon Lookout for Metrics 

AWS Machine Learning Blog

The service, which was launched in March 2021, predates several popular AWS offerings that have anomaly detection, such as Amazon OpenSearch , Amazon CloudWatch , AWS Glue Data Quality , Amazon Redshift ML , and Amazon QuickSight. To use this feature, you can write rules or analyzers and then turn on anomaly detection in AWS Glue ETL.

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Bundesliga Match Facts Shot Speed – Who fires the hardest shots in the Bundesliga?

AWS Machine Learning Blog

To achieve this, our process uses a synchronization algorithm that is trained on a labeled dataset. This algorithm robustly associates each shot with its corresponding tracking data. Shot speed calculation The heart of determining shot speed lies in a precise timestamp given by our synchronization algorithm.

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Big data engineering simplified: Exploring roles of distributed systems

Data Science Dojo

Different algorithms and techniques are employed to achieve eventual consistency. Amazon S3: Amazon Simple Storage Service (S3) is a scalable object storage service provided by Amazon Web Services (AWS). They use redundancy and replication to ensure data availability.

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Anomaly detection in streaming time series data with online learning using Amazon Managed Service for Apache Flink

AWS Machine Learning Blog

In this post, we demonstrate how to build a robust real-time anomaly detection solution for streaming time series data using Amazon Managed Service for Apache Flink and other AWS managed services. It offers an AWS CloudFormation template for straightforward deployment in an AWS account.

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Use streaming ingestion with Amazon SageMaker Feature Store and Amazon MSK to make ML-backed decisions in near-real time

AWS Machine Learning Blog

We use Amazon SageMaker to train a model using the built-in XGBoost algorithm on aggregated features created from historical transactions. Apache Flink is a popular framework and engine for processing data streams. Prerequisites We provide an AWS CloudFormation template to create the prerequisite resources for this solution.

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How Netflix Applies Big Data Across Business Verticals: Insights and Strategies

Pickl AI

It utilises Amazon Web Services (AWS) as its main data lake, processing over 550 billion events daily—equivalent to approximately 1.3 Data in Motion Technologies like Apache Kafka facilitate real-time processing of events and data, allowing Netflix to respond swiftly to user interactions and operational needs. petabytes of data.