AI-Ready Bricks are plug-and-play AI/ML pipelines built on the Microsoft Azure machine learning (ML) platform. Users can learn, build and deploy simple ML solutions using these Bricks as a foundation. Similar solutions can be built on other AI/ML cloud platforms from Google Cloud and AWS.


1. Time-Series Demand Forecast

Demand forecast is a common function performed by sales organizations. This experiment shows how a machine learning model can be used to forecast demand for a bike rental company.

2. E-commerce Product Recommender

Recommends products based on user interactions and user-product metadata.

3. Customer Segmentation

Customer segmentation groups customers based on their attributes. This gives customer insights and enables targeted marketing.

4. Customer Churn Prediction

The ability to predict which customers will churn is an important competitive advantage for businesses. This ability will allow the marketing department to focus its intervention efforts more appropriately. This experiment shows how a machine learning model can be built to predict customer churn for a telco.

5. Personal Credit Risk Classification

Credit risk classification predicts the credit score of borrowers. The insight can help the bank make better decisions.

6. Corporate Credit Risk Prediction

Predicts the credit risk for corporate suppliers and customers based on historical data.

Keen To Learn?

We have shown simple examples of ML use cases here which can form the foundation of your solution. You can learn more about Data Analytics with our free Data Analytics For Everyone (DA4E) and AI course over at our LearnAI site. Please also join our Community forums to build your network and knowledge!