Introducing MLOps to Facilitate the Development of Machine Learning Models in Agronomy: A Case Study

Introducing MLOps to Facilitate the Development of Machine Learning Models in Agronomy: A Case Study

While machine learning (ML) and deep learning (DL) are increasingly being adopted in agronomy, the literature shows that the use of ML Operations (MLOps) frameworks remains scarce during the research stage. This study discusses the utility of MLOps in enhancing the reproducibility and transparency o...

Full description

Saved in:
Bibliographic Details
Main Authors: Dario Ruggeri, Gabriele Tazza, Laszlo Vidacs
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Agronomy
ClearML
crop science
deep learning
Docker
foodomics
Online Access:https://ieeexplore.ieee.org/document/11072436/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/11072436/

Similar Items