Machine Learning with Metadata and Experimental Citizen Science in R

Machine learning is the scientific study of algorithms and statistical models that provides the computer the ability to automatically learn and improve from experience. During the 2020 CGIAR-CSI Community Meeting, Kauê de Sousa, Research Fellow from Bioversity-CIAT Alliance, presented a set of tools developed to facilitate the analysis of metadata and experimental citizen science data, from collating data of different sources, gathering environmental variables, to model selection and visualization. All in a single pipeline in R that can be automated to improve predictions and recommendations for agriculture.

Kauê’s presentation slide is available to download here. All data and R code files are available at https://github.com/agrobioinfoservices.