AWS woos developers and their data lake wants and needs, follows Microsoft Azure’s February machine learning release
Amazon Web Services has announced it’s going to offer its customers machine learning, allowing developers to use historical data to build and deploy predicative models on AWS.
Revealed at San Francisco’s AWS Summit, the release is hot on the heels of Microsoft Azure’s machine learning platform, which was launched in February of this year.
“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.”
Amazon 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.
“Amazon Machine Learning makes machine learning broadly accessible to all software developers by abstracting away this complexity and automating these steps,” said the company.