AgML - Machine Learning for Agricultural Modeling

AgML is the AgMIP transdisciplinary community of agricultural and machine learning modelers.

AgML aspires to

• identify key research gaps and opportunities at the intersection of agricultural modelling and machine learning research,
• support enhanced collaboration and engagement between experts in these disciplines, and
• conduct and publish protocol-based studies to establish best practices for robust machine learning use in agricultural modelling.

AgML Tasks

Tasks	Working Document	GitHub Repository
Subnational crop yield forecasting	Subnational crop yield forecasting	AgML-crop-yield-forecasting
Climate change projections of agricultural yields

For more information please visit the AgML website.