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AgML aspires to identify key research gaps and opportunities at the intersection of agricultural modelling and machine learning research and support enhanced collaboration and engagement between experts in these disciplines.

Home Page: https://www.agml.org/

agricultural-modeling crop-yield machine-leanring

agml's Introduction

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.

agml's People

Contributors

Stargazers

Watchers

agml's Issues

Add a guide for contributing to AgML

A guide for

How to become a collaborator
How to open an issue, work on it, create a pull request and merge changes
How to onboard a dataset
How to submit a model for benchmarking
3 and 4 could follow the same procedure as 2.

Add contributors to the repository

Adding collaborators or team members requires them to be part of AgMIP organization. AgML team members need permissions to add members to AgMIP organization. We could also check other ways to add team members or collaborators.

Add a data card template

Decide the minimal and extended template
Decide the display format

Decide the general structure of the repository

Should we go with something like this?

agml/
agml/benchmark_tasks/
agml/models/
docs/

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