How to Use Data Science in Agriculture to Predict Yield and Diseases
Data science has a great potential to add values to the agriculture sector. Applying data science in agriculture includes two major sections; data analytics and machine learning. This post brings real examples of how to use data analytics to visualize main effects and interactions. It, also, provides practical applications of predictive analytics and machine learning for yield and severity of diseases in wheat.
