AWS Machine Learning Goes Live In Europe

Amazon Web Services’ (AWS) machine learning service has gone live in Europe, allowing developers to use historical data to build and deploy predicative models on AWS.

First revealed at San Francisco’s AWS Summit, the release follows Microsoft Azure’s machine learning platform, which was launched in February of this year. The European service is hosted in Amazon’s Dublin data centre.

“Using Amazon Machine Learning in the Dublin region, that is nearest to our European customer’s predictive applications, helps with lower real-time prediction latencies,” said AWS.

Analytics and predictions

“Further, availability of Amazon Machine Learning in this region helps to address limitations organisations may have related to the location of their data as all analytics and predictions will be done on data that resides in Europe and will not leave the region.”

Machine Learning is integrated with Amazon Simple Storage Service (Amazon S3), Amazon Redshift and Amazon Relational Database Service (Amazon RDS), and developers can use the AWS Management Console or APIs to create as many models as they need, and generate predictions from them.

Amazon said that until now, it’s been tricky for developers to build applications with machine learning functions because doing so required expertise in data sciences.

“Early on, we recognised that the potential of machine learning could only be realised if we made it accessible to every developer across Amazon, Jeff Bilger, Senior Manager, Amazon Machine Learning.

Amazon Machine Learning is the result of everything we’ve learned in the process of enabling thousands of Amazon developers to quickly build models, experiment, and then scale to power planet-scale predictive applications.”

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Ben Sullivan

Ben covers web and technology giants such as Google, Amazon, and Microsoft and their impact on the cloud computing industry, whilst also writing about data centre players and their increasing importance in Europe. He also covers future technologies such as drones, aerospace, science, and the effect of technology on the environment.

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