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This article discusses how machine learning algorithms are being used to make more accurate crop yield predictions in the agriculture industry. Linear regression, decision trees, random forests, support vector machines, and neural networks are some of the algorithms being used to make these predictions. These algorithms are able to capture complex and nonlinear patterns in the data, as well as handle missing values and outliers.
