Análisis de métodos de ML para el desarrollo de un sistema recomendador en la producción de rosas

Abstract

The importance of predicting soil nutrients is of great interest in agriculture; this work proposes the implementation of three ML classifiers to label soil nutrient values, as well as the implementation of these models in conjunction with a recommender system using a language extensive model such as Gemini AI.