Machine Learning as a Service: Amazon

I can’t wait to get my hands on Amazon Machine Learning service that was launched on Friday Apr 10, 2015. Apparently in an internal experiment they found that it took some of their developers 20 minutes to solve a problem that took another pair 45 days. They say that none of these developers had prior experience in machine learning, and both models apparently achieved the same accuracy of 92 percent. No matter how you look at it, that seems exaggerated. Hence, my peaked curiosity to play with it in the coming days. I will post results and experience here soon.

In the meantime, if you are wondering what can they be used for, below are some of Amazon’s suggested use cases.

Propensity Modeling for Marketing Campaigns

Use it to deliver targeted marketing campaigns, for example: Amazon Machine Learning could use prior customer activity to choose the most relevant email campaigns for target customers.

Content Personalization

Leverage it to make websites provide a more personalized customer experience by using predictive models to recommend items or optimize website flow based on prior customer actions.

Document Classification

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.

Automated Solution Recommendation for Customer Support

Process free-form feedback from customers, including email messages, comments or phone conversation transcripts, and recommend actions that can best address their concerns. For example, use it to analyze social media traffic to discover customers who have a product support issue, and connect them with the right customer care specialists.

Fraud Detection

Build predictive models that help identify potentially fraudulent retail transactions, or detect fraudulent or inappropriate item reviews.

Customer Churn Prediction

Leverage it to find customers who are at high risk of attrition, you can then use it to proactively engage them with promotions or customer service outreach.