Pinned Repositories
AgML-CY-Bench
CY-Bench (Crop Yield Benchmark) is a comprehensive dataset and benchmark to forecast crop yields at subnational level. CY-Bench standardizes selection, processing and spatio-temporal harmonization of public subnational yield statistics with relevant predictors. Contributors include agronomers, climate scientists and machine learning researchers.
BigDataMOOC
The tutorials for the edX course Big Data for Agri-Food: Principles and Tools
crop-gym
An OpenAI gym environment for crop management
Domain-adaptation-for-pasture-digital-twins
EDAM
EDAM (Environmental Data Acquisition Module) is a template framework that facilitates timeseries data acquisition and integration
ML4ClimateAdaptationPolicy
MLforCropYieldForecasting
Implementation of Machine learning baseline for large-scale crop yield forecasting
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
simulation-assisted-ML
Implementation for the paper 'Simulation-assisted machine learning for operational digital twins'
tomatula
BigDataWUR's Repositories
BigDataWUR/MLforCropYieldForecasting
Implementation of Machine learning baseline for large-scale crop yield forecasting
BigDataWUR/crop-gym
An OpenAI gym environment for crop management
BigDataWUR/tomatula
BigDataWUR/AgML-CY-Bench
CY-Bench (Crop Yield Benchmark) is a comprehensive dataset and benchmark to forecast crop yields at subnational level. CY-Bench standardizes selection, processing and spatio-temporal harmonization of public subnational yield statistics with relevant predictors. Contributors include agronomers, climate scientists and machine learning researchers.
BigDataWUR/EDAM
EDAM (Environmental Data Acquisition Module) is a template framework that facilitates timeseries data acquisition and integration
BigDataWUR/simulation-assisted-ML
Implementation for the paper 'Simulation-assisted machine learning for operational digital twins'
BigDataWUR/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
BigDataWUR/ML4ClimateAdaptationPolicy
BigDataWUR/BigDataMOOC
The tutorials for the edX course Big Data for Agri-Food: Principles and Tools
BigDataWUR/Domain-adaptation-for-pasture-digital-twins
BigDataWUR/locomotiondatalake
Software accompanying the paper "Storing, combining, and analysing animal experimental data in the big data era"
BigDataWUR/BigDataMOOC_content
BigDataWUR/MapReduceIslandGame
An interactive game for Map-Reduce
BigDataWUR/A-scab
BigDataWUR/Advanced-Machine-Learning-Course
BigDataWUR/sample_data