Predictive Analytics: Case Studies for AI in Agriculture

Skillsoft issued completion badges are earned based on viewing the percentage required or receiving a passing score when assessment is required. Population growth, climate change, and volatile commodity prices risk factors are putting a strain on the agricultural system nowadays. Using artificial intelligence (AI) in agriculture can potentially help mitigate this strain in areas such as yield prediction and disease detection in agriculture. In this course, explore a study that uses machine learning (ML) models for agricultural use cases. Next, explore a specific case study that attempts to predict the yield of maize and soybean crops on various American farms. Finally, examine a study that uses machine learning for pest detection. Upon completion, you'll be able to gather and analyze academic papers on machine learning in agriculture, identify problem categories and solution constructs, and recall common recurring themes in research.