machine learning models

Machine learning models learn patterns and relationships from data to make predictions or decisions. The quality of the data influences how well these models can represent and generalize

Machine learning models must first be trained.  That training results in a model which must be serialized or packaged up in some way as a deployment artifact.  A popular deployment

The incredible advances in machine learning research in recent years often take time to propagate out into usage in the field. One reason for this is that such “state-of-the-art”

Machine learning models require training data, and training data needs to be labeled. Raw images and text can be labeled using a training data platform like Labelbox. Labelbox is a

Machine learning models are only as good as the datasets they’re trained on. Aquarium is a system that helps machine learning teams make better models by improving their dataset