AWS Partner Network (APN) Blog

Machine Learning on the AWS Cloud

The following is a guest post from one of our APN SAs. This post is an introductory, high-level post. It is intended to help APN Partners familiarize themselves with the concept of machine learning, and to learn more about the use cases that can be supported using Amazon Machine Learning.  


There can be tremendous amounts of information buried within gigabytes of your data, including web site visitor metrics, sales information, and email campaign responses, to name a few. How do you tap into that information to make informed business decisions? Is there a way an organization can take advantage of its existing repositories of data to predict the choices customers may make in the future?

Machine learning (ML) can help you use historical data to make better business decisions. ML algorithms discover patterns in data, and construct mathematical models using these discoveries. With machine learning, you can use these models to make predictions on future data. For example, one possible application of a machine learning model would be to predict how likely a customer is to purchase a particular product based on their past behavior.

Smart Applications

Machine learning is the technology that can find patterns in data and use them to make predictions for new data points as they become available. A simplistic definition of a smart application:

Your data + machine learning = smart applications

Smart applications can predict future user action based on past actions. For example, based upon what it knows about the user, a smart application can predict whether the user will make a purchase. A lot of banks are using a smart application concept to warn a user if their log in pattern changes. It’s not uncommon in retail banking websites to see a warning whenever a user tries to log in from a different location or computer. Another example can be seen in specific recommendations made to users from a website; a number of e-commerce and news aggregation websites offer recommendations on a product or news that might be interesting for the user.

The science of machine learning provides the mathematical underpinnings needed to run the analysis and to make sense of the results.  It can help you turn your data into high-quality predictions by finding and codifying patterns and relationships within the data.

What is Amazon Machine Learning?

Amazon Machine Learning is a service that that makes it easy for developers of all skill levels to use machine learning technology, based on the same proven, highly scalable, ML technology used for years by Amazon’s internal data scientist community.  Amazon Machine Learning allows you to easily build predictive applications, including fraud detection, demand forecasting, and click prediction. Amazon Machine Learning uses powerful algorithms that can help you create machine-learning models by finding patterns in existing data, and using these patterns to make predictions from new data as it becomes available.

You can use Amazon Machine Learning through the AWS Management Console and access the data and model visualization tools, as well as wizards, to guide you through the process of creating machine learning models, measuring their quality, and fine-tuning the predictions to match your application requirements. Once the models are created, you can get predictions for your application by using the simple Amazon Machine Learning API, without having to implement custom prediction generation code or manage any infrastructure.

Amazon Machine Learning is highly scalable, and can generate billions of predictions, and serve those predictions in real-time and at high throughput. With Amazon Machine Learning there is no setup cost and you pay as you go, so you can start small and scale as your application grows.

Popular Amazon ML Use Cases

There are a number of use cases for which Machine Learning is a good fit. For APN Partners, I recommend that you consider how smart applications may enhance the value you’re able to provide for your customers on AWS in the following areas, which are outlined on our main Amazon Machine Learning page in more detail: Fraud Detection, Content Personalization, Propensity Modeling for Marketing Campaigns, Document Classification, Customer Churn Prediction, and Automated Support Recommendation for Customer Support.


To find out more about Amazon Machine Learning, visit the service web pages and get started building your first predictive model, today.