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Bibliographic Details
Main Authors: Ferianc, Martin, Rodrigues, Miguel
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2402.06268
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author Ferianc, Martin
Rodrigues, Miguel
author_facet Ferianc, Martin
Rodrigues, Miguel
contents YAMLE: Yet Another Machine Learning Environment is an open-source framework that facilitates rapid prototyping and experimentation with machine learning (ML) models and methods. The key motivation is to reduce repetitive work when implementing new approaches and improve reproducibility in ML research. YAMLE includes a command-line interface and integrations with popular and well-maintained PyTorch-based libraries to streamline training, hyperparameter optimisation, and logging. The ambition for YAMLE is to grow into a shared ecosystem where researchers and practitioners can quickly build on and compare existing implementations. Find it at: https://github.com/martinferianc/yamle.
format Preprint
id arxiv_https___arxiv_org_abs_2402_06268
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle YAMLE: Yet Another Machine Learning Environment
Ferianc, Martin
Rodrigues, Miguel
Machine Learning
YAMLE: Yet Another Machine Learning Environment is an open-source framework that facilitates rapid prototyping and experimentation with machine learning (ML) models and methods. The key motivation is to reduce repetitive work when implementing new approaches and improve reproducibility in ML research. YAMLE includes a command-line interface and integrations with popular and well-maintained PyTorch-based libraries to streamline training, hyperparameter optimisation, and logging. The ambition for YAMLE is to grow into a shared ecosystem where researchers and practitioners can quickly build on and compare existing implementations. Find it at: https://github.com/martinferianc/yamle.
title YAMLE: Yet Another Machine Learning Environment
topic Machine Learning
url https://arxiv.org/abs/2402.06268