Fully Automating Server-side Object Detection Workflows

Continuing with our Object Detection release blog posts series, today, we'll showcase how to automate the training of the object detection models (and their predictions) that anyone will be able to create in BigML in short order. As discussed in previous posts, BigML already offers classification, regression, and unsupervised learning models (e.g., clustering, anomaly detection). They all accept images as just another input data type usable for model training. In fact, when images are uploaded a new Source is created for each and their corresponding IDs are added to a new Composite Source object with a new image field type. In summary, images can be combined with any other data type and can be assigned one or more labels by using the new label fields.