Predictive Analytics: Performing Prediction Using Regression

In agriculture accurately assessing crop yield in advance can help farmers effectively plan ahead allocate labor and capital and plan for crop transportation logistics. Machine learning (ML) can be used to account for the many factors that drive yields. In this course work with data consisting of blueberry plant information and climate factors to predict yield. Next learn how to visualize univariate relationships and bivariate correlations and perform linear regression. Finally practice performing feature selection for the regression model and view the score of importance and model on a subset for different data attributes. Upon completion youll be able to use regression techniques to predict agricultural yields identify real-world and statistical relationships in the data and differentiate between various regression models.