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. In this workshop, we will work in a set of tools developed by Bioversity-CIAT 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. All data and R code files are available at https://github.com/agrobioinfoservices.

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