Published December 5, 2022 | Version 1
Software Open

Yield Prediction Through Integration of Genetic, Environment, and Management Data Through Deep Learning: Computational Artifacts

Authors/Creators

  • 1. USDA-ARS

Description

The included files and script are to allow for reconstruction of the project structure and code used in "Yield Prediction Through Integration of Genetic, Environment, and Management Data Through Deep Learning" ( https://doi.org/10.1101/2022.07.29.502051 ). Data is included separately at 10.5281/zenodo.6916775.

Filename Description
.git.tar.gz Zipped git history
.gitignore  
data.tar.gz Placeholder. Data from 10.5281/zenodo.6916775 should be unzipped into this folder
models.tar.gz Models training and hyperparameter optimization
notebooks.tar.gz Notebooks (Jupyter and Rmd) for data cleaning and analysis
output.tar.gz Placeholder. Figures and tables are written into this folder
README.md High level project organization
SetupInstructions.sh Helper script to unzip folders

This work was supported through funding from the USDA Agricultural Research Service, ARS project number 5070-21000-041-000-D.

Files

README.md

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