These examples are created to help you through the VisRec API even better. Most of these examples are covered in our "Getting Started" document which we published at
https://github.com/JavaVisRec/visrec-api/wiki/Getting-Started-Guide.
We highly recommend you to read that article especially if you're a beginner to machine learning but it's not mandatory to read that document get started.
The Visual Recognition API JSR #381 is a software development standard recognized by the Java Community Process (JCP) that simplifies and standardizes a set of APIs familiar to Java developers for classifying and recognizing objects in images using machine learning. Beside classes specific for visual recognition tasks, it provides general abstractions for machine learning tasks like classification, regression and data set, and reusable design which can be applied for machine learning systems in other domains. At the current stage it provides basic hello world examples for supported machine learning tasks (classification and regression) and image classification.
Specification for VisRec API is available at
https://github.com/JavaVisRec/visrec-api
Reference implementation of specification is available at
https://github.com/JavaVisRec/visrec-ri/
Reference implementation is based on community edition of Deep Netts Deep Learning Engine available at
https://github.com/deepnetts/deepnetts-communityedition