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ModelOp Center provides plugins into common data science development tools such as Jupyter, to allow data scientists to interact with ModelOp Center from their preferred development environment.

Table of Contents

Table of Contents

Using ModelOp Center Jupyter plugin
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Overview

The ModelOp Center (MOC) is flexible on how models are registered so that data scientists can leverage their preferred environments for model creation. In other words it is agnostic to the toolkit used to create the model.

Jupyter (http://jupyter.org/) is a popular tool among data scientists and other users of Python and R for building models. It is an evolution of the IPython project, and provides a Notebook interface similar to that of Mathematica or SAGE. For the purposes of the interaction between ModelOp Center and Jupyter we have the Jupyter plugin available which makes it easier to make some of the most useful operations directly in the user’s IDE of choice, in this case, Jupyter notebook.

Installation and configuration instructions

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Jupyter plugin installation and configuration instructions
Jupyter plugin installation and configuration instructions

ModelOp specific functions available within Jupyter

Once installed, when the user opens or creates a new Jupyter notebook file, the Jupyter notebook interface is provided with a set of toolbar buttons that interact with ModelOp Center and will be expanded in the sections below.

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Registering a new model

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Registering a model using Jupyter
Registering a model using Jupyter

Opening an existing model

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Opening an existing model in Jupyter
Opening an existing model in Jupyter

Updating an existing model

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Updating an existing model using Jupyter
Updating an existing model using Jupyter

Submit model version

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Submit model version using Jupyter
Submit model version using Jupyter

Table of Contents

Table of Contents