BigDataWUR

MLforCropYieldForecasting

Implementation of Machine learning baseline for large-scale crop yield forecasting

crop-gym

An OpenAI gym environment for crop management

tomatula

AgML-crop-yield-forecasting

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.

EDAM

EDAM (Environmental Data Acquisition Module) is a template framework that facilitates timeseries data acquisition and integration

simulation-assisted-ML

Implementation for the paper 'Simulation-assisted machine learning for operational digital twins'

ML4ClimateAdaptationPolicy

PCSE-Gym

CropGym is a highly configurable Python gymnasium environment to conduct Reinforcement Learning (RL) research for crop management. CropGym is built around PCSE, a well established python library that includes implementations of a variety of crop simulation models

BigDataMOOC

The tutorials for the edX course Big Data for Agri-Food: Principles and Tools

Domain-adaptation-for-pasture-digital-twins

locomotiondatalake

Software accompanying the paper "Storing, combining, and analysing animal experimental data in the big data era"

BigDataMOOC_content

MapReduceIslandGame

An interactive game for Map-Reduce

sample_data