As a business user or data analyst, you’d like to build and use prediction systems based on the data that you analyze and process every day, without having to learn about hundreds of algorithms, training parameters, evaluation metrics and deployment best practices.

At this year’s re:Invent in Las Vegas, AWS announced the general availability of Amazon SageMaker Canvas, a new visual, no code capability that allows business analysts to build ML models and generate accurate predictions without writing code or requiring ML expertise. Its intuitive user interface lets you browse and access disparate data sources in the cloud or on-premises, combine datasets with the click of a button, train accurate models and then generate new predictions once new data is available.

SageMaker Canvas leverages the same technology as Amazon SageMaker to automatically clean and combine your data, create hundreds of models under the hood, select the best performing one and generate new individual or batch predictions. It supports multiple problem types such as binary classification, multi-class classification, numerical regression and time series forecasting. These problem types let you address business-critical use cases, such as fraud detection, churn reduction and inventory optimization, without writing a single line of code!