A collection of machine learning templates for solving domain specific industrial problems with Azure ML Studio is presented here.
##What is a Machine Learning Template? A machine learning template demonstrates the standard industry practices and common building blocks in building a machine learning solution for a specific domain, starting from **data preparation, data processing, feature engineering, model training** to **model deployment**. The goal of the templates is to enable data scientists to quickly build and deploy custom machine learning solutions with Azure Machine Learning platform, and increase their productivity with a higher starting point. The template includes a collection of pre-configured Azure ML modules, as well as custom R scripts in the Execute R Script modules, to enable an end-to-end solution. Each template includes the following: * A data schema (with sample dataset) applicable to the specific domain * Domain specific data processing and feature engineering steps * Models training algorithms fit to the specific domain * Domain specific evaluation metric (if applicable) * Model deployment as a web service Iterative in nature, and for ease of understanding and experimentation to the user, each template is put into multiple steps (and multiple experiments) and have detailed documentation and instructions on how to use the template in the Azure ML Gallery. ## What templates are available The Microsoft machine learning team has created the following templates: - **Predictive Maintenance**. Predict machine failures. - **Customer Churn Prediction**. Predict when a customer churn happens. - **Online Purchase Fraud Detection**. Predict if an online purchase transactions is fraudulent. - **Retail Forecasting**. Forecast the product sales for a retail store. - **Text Classification**. Classify text records into two different classes (e.g., twitter sentiment) Check these out and have fun!