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.
To simplify machine learning for developers and data scientists, AWS now offers Amazon SageMaker, a fully-managed service with sophisticated development, training, and hosting features that lets developers focus on the data science of building, training, and tuning machine learning models without having to worry about infrastructure or system management.
Easily Create Machine Learning Models
Amazon Machine Learning APIs and wizards make it easy for any developer to create and fine-tune ML models from data stored in Amazon S3, Amazon Redshift or 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.
From Models to Predictions in Seconds
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.
Scalable, High Performance Prediction Generation Service
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 makes it easy to build predictive models that help identify potentially fraudulent retail transactions, or detect fraudulent or inappropriate item reviews.
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.
Propensity Modeling for Marketing Campaigns
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.
Customer Churn Prediction
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.
Automated Solution Recommendation for Customer Support
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.
Amazon SageMaker for Machine Learning
Amazon SageMaker is a fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.