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Model Object, Optimized (MOJO)

What is a MOJO? MOJO (stands for Model Object, Optimized) [1] is a standalone, low-latency model object designed to be easily embeddable in production environments. In Driverless AI , the MOJO Model is combined with a feature engineering pipeline to create a MOJO scoring pipeline ...

Scoring Pipeline

What is a Scoring Pipeline? In machine learning , pipelines are the automation of sequential steps in a workflow. These steps may include data preparation , model training , validation , packaging , deployment as well as monitoring. A scoring pipeline is usually a part of the deployment...

Scoring / Making Predictions / Inferencing

What is Scoring? Scoring, also known as inferencing, is the process of using a trained machine learning model to make predictions based on input data. There are two types of scoring: batch scoring and real-time scoring. Batch scoring involves using the model to make predictions on multiple...

Machine Learning Model

What is a Machine Learning Model? A machine learning model is generated by either supervised or unsupervised training. It is an abstract representation of relationships between variables learned from data. Once trained , a machine learning model can be used to make predictions based on...