Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology. Amazon Machine Learning provides visualization tools and wizards that guide you through the process of creating machine learning (ML) models without having to learn complex ML algorithms and technology. Once your models are ready, Amazon Machine Learning makes it easy to obtain predictions for your application using simple APIs, without having to implement custom prediction generation code, or manage any infrastructure.
Amazon Machine Learning is based on the same proven, highly scalable, ML technology used for years by Amazon’s internal data scientist community. The service uses powerful algorithms to create ML models by finding patterns in your existing data. Then, Amazon Machine Learning uses these models to process new data and generate predictions for your application.
Amazon Machine Learning is highly scalable and can generate billions of predictions daily, and serve those predictions in real-time and at high throughput. With Amazon Machine Learning, there is no upfront hardware or software investment, and you pay as you go, so you can start small and scale as your application grows.
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Please note that Amazon Machine Learning is not currently available on the AWS Free Tier.
Read "Why Our Customers Love Amazon Machine Learning", a guest post from the CEO of AWS Partner 47Lining.
AWS Case Study: AdiMap & Amazon Machine Learning
As a startup, AdiMap uses Amazon Machine Learning to provide "users and customers with a competitive advantage by offering financial intelligence at scale".
AWS Case Study: Fraud.net & Amazon Machine Learning
As a leading crowdsourced fraud prevention platform, Fraud.net uses Amazon Machine Learning to help reduce complexity and make sense of emerging fraud patterns.
Amazon Machine Learning APIs and wizards make it easy for any developer to create and fine-tune ML models from data stored in Amazon Simple Storage Service (Amazon S3), Amazon Redshift, or MySQL databases in Amazon Relational Database Service (Amazon RDS), and query these models for predictions. The service’s built-in data processors, scalable ML algorithms, interactive data and model visualization tools, and quality alerts help you build and refine your models quickly.
Amazon Machine Learning is a managed service that provides end-to-end model creation, deployment, and monitoring. Once your model is ready, you can quickly and reliably generate predictions for your applications, eliminating the time and investment needed to build, scale, and maintain machine learning infrastructure.
Amazon Machine Learning prediction APIs can be used to generate billions of predictions for your applications. You can request predictions for large numbers of data records all at once using the batch prediction API, or use the real-time API to obtain predictions for individual data records, and use them within interactive web, mobile, or desktop applications.
Amazon Machine Learning is based on the same proven, highly scalable, ML technology used by Amazon to perform critical functions like supply chain management, fraudulent transaction identification, and catalog organization.
Amazon Machine Learning can help your website provide a more personalized customer experience by using predictive analytics models to recommend items or optimize website flow based on prior customer actions.
Amazon Machine Learning can help you deliver targeted marketing campaigns. For example, Amazon Machine Learning could use prior customer activity to choose the most relevant email campaigns for target customers.
Amazon Machine Learning can help you process unstructured text and take actions based on content. For instance, Amazon Machine Learning could be used to build applications that classify product reviews as positive, negative, or neutral.
Amazon Machine Learning can help you find customers who are at high risk of attrition, enabling you to proactively engage them with promotions or customer service outreach.
Amazon Machine Learning can process free-form feedback from your customers, including email messages, comments or phone conversation transcripts, and recommend actions that can best address their concerns. For example, you can use Amazon Machine Learning to analyze social media traffic to discover customers who have a product support issue, and connect them with the right customer care specialists.