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Jaqpot 5: How to deploy a predictive model using the jaqpotpy library

Haralambos Sarimveis

Contact person(s)
Pantelis Karatzas; Philip Doganis

Jaqpot 5 is a user-friendly web-based e-infrastructure that allows model developers to deploy their predictive models and share them through the web. The Jaqpot 5 GUI  directs the model developers to further document their models in a way that can be easily understood and used by end-users with little or no experience on machine learning and statistical analysis.   The GUI also allows the end-users to apply the models on their own data for validation and/or prediction purposes and the results are collected and visualised in automatically generated tables, graphs and reports. All major machine learning and statistical data-driven algorithms are supported in Jaqpot 5,  by integrating popular libraries such as the Python Scikit-learn and the R Caret libraries. Jaqpot 5 has been designed as a generic modelling and machine learning web platform, but particular emphasis is given on serving the needs of the chemo/bio/nano/pharma/ communities by integrating QSAR, biokinetics, dose-response and read-across models.  Jaqpot 5 has been developed by the Unit of Process Control and Informatics in the School of Chemical Engineering at the National Technical University of Athens.

 

This document provides a tutorial on how to deploy a model in Jaqpot 5 using the jaqpotpy library. The resource has been made available at https://app.jaqpot.org/.

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