Predictive Analytics in Agriculture Competency (Intermediate Level)

Topics covered

• classify types using machine learning (ML)
• cluster crop data using agglomerative clustering
• examine data for blueberry yields
• fine-tune the clustering of climatic data
• identify attributes that help with yield prediction
• import data on wild blueberry yields
• improve crop yield prediction using different machine learning (ML) models
• optimize the clustering of climatic data
• perform feature selection for classification
• perform k-means clustering on climatic data
• perform transformations on blueberry yield data
• predict blueberry yield using linear regression
• select the most important attributes for classification
• set up a classifier
• set up a climatic condition clustering model
• set up clustering for climatic data
• set up data for performing classification
• transform crop data for clustering
• view attribute relationships in the data
• view relationships between climatic conditions
• visualize data about a crop's climatic conditions