iMESc: an Interactive Machine Learning App for Environmental Science

 iMESc is a shiny-based application which implements a range of algorithms for data pre-processing, analysis, and visualization. To optimize learning from the data, iMESc allows the adjustment of the analytical parameters of each ML algorithm  by means of a context-aware dynamic interface.  Throughout the software, data input and results output are organized in modules enabling the creation of multiple ML pipelines . iMESc also offers users classical statistical approaches, such as principal component analysis and non-metric multidimensional scale, calculation of traditional biodiversity indexes and the spatialization of the data on the geographical coordinate plan. By having a common platform that facilitates the implementation of machine learning techniques, such as iMESc, it will help the scientific community to develop more reproducible workflows and, consequently, promote a faster scientific progress.