Predictive Analytics: Applying Clustering to Soil Features & Conditions

The question of what crops ought to be planted per growing season for a given patch of land is extremely important. An important related question is which type of crop fits most easily with the soil and climatic conditions. Machine learning (ML) models like clustering can help answer this question using data from other farms. In this course work with soil data consisting of field climate conditions. Next learn how to use charts to view univariate information and the relationships between attributes. Finally discover how to perform k-means and agglomerative clustering on data. Upon completion youll be able to apply clustering to data identify links between clusters identified by ML algorithms and the crops cultivated in them and differentiate k-means and agglomerative clustering.