It’s a fully managed service that makes it easy for any developer to use historical data to build and deploy predictive models
Amazon Web Services has launched Amazon Machine Learning, a fully managed service that makes it easy for any developer to use historical data to build and deploy predictive models.
These models can be used for a broad array of purposes, including detecting problematic transactions, preventing customer churn, and improving customer support announced the press release. Based on the same proven, highly scalable machine learning technology used by developers across Amazon to generate more than 50 billion predictions a week, Amazon Machine Learning’s APIs and wizards guide developers through the process of creating and tuning machine learning models that can be easily deployed and scale to support billions of predictions.
Amazon Machine Learning is integrated with Amazon Simple Storage Service (Amazon S3), Amazon Redshift and Amazon Relational Database Service (Amazon RDS), making it easy for customers to work with the data they’ve already stored in the AWS Cloud. To get started with Amazon Machine Learning, visit http://aws.amazon.com/machine-learning.
With Amazon Machine Learning, developers can use the AWS Management Console or APIs to quickly create as many models as they need, and generate predictions from them with high throughput without worrying about provisioning hardware, distributing and scaling the computational load, managing dependencies, or monitoring and troubleshooting the infrastructure. There is no setup cost, and developers pay as they go so they can start small and scale as an application grows.
Jeff Bilger, Senior Manager, Amazon Machine Learning, said, “Early on, we recognized that the potential of machine learning could only be realized if we made it accessible to every developer across Amazon. 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.”
