5 Hands-on 3: Introduction to developing Python computational pipelines for predictive machine learning modelling of livestock data

Abstract This hands-on workshop aims to offer examples of computational pipelines that apply traditional predictive machine learning modelling techniques to animal science datasets with the purpose of solving classification and/or regression problems. The objective of this workshop is to provide the attendants with fully functional and customizable computational pipelines developed in Python. The workshop is structured in a hands-on format and includes a combination of basic notions about machine learning and relevant algorithms, evaluation measures, evaluation strategies and Python code examples. To avoid technical problems related to installing a Python environment on personal computers, we recommend the registrants to acquire access on the Repl.it platform (https://replit.com/) by creating a free account prior to attending the workshop. Detailed information will be provided before the beginning of the workshop at the following URL: http://animalbiosciences.uoguelph.ca/~dtulpan/conferences/asas2024/

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Publication Details

Journal
Journal of Animal Science
Published
2024-09-01
DOI
https://doi.org/10.1093/jas/skae234.076
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
Field-Weighted Citation Impact
0.00
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article

5 Hands-on 3: Introduction to developing Python computational pipelines for predictive machine learning modelling of livestock data

Dan Tulpan
Journal of Animal Science
Genetic and phenotypic traits in livestock
article

5 Hands-on 3: Introduction to developing Python computational pipelines for predictive machine learning modelling of livestock data

Dan Tulpan
article en

Abstract

Abstract This hands-on workshop aims to offer examples of computational pipelines that apply traditional predictive machine learning modelling techniques to animal science datasets with the purpose of solving classification and/or regression problems. The objective of this workshop is to provide the attendants with fully functional and customizable computational pipelines developed in Python. The workshop is structured in a hands-on format and includes a combination of basic notions about machine learning and relevant algorithms, evaluation measures, evaluation strategies and Python code examples. To avoid technical problems related to installing a Python environment on personal computers, we recommend the registrants to acquire access on the Repl.it platform (https://replit.com/) by creating a free account prior to attending the workshop. Detailed information will be provided before the beginning of the workshop at the following URL: http://animalbiosciences.uoguelph.ca/~dtulpan/conferences/asas2024/

Journal of Animal ScienceVol. 102(Supplement_3)
University of Guelph (CA)
Openalex Percentile: Top 83%
Genetic and phenotypic traits in livestock
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5 Hands-on 3: Introduction to developing Python computational pipelines for predictive machine learning modelling of livestock data — Dan Tulpan · Journal of Animal Science (2024) | TGRS Research Map | TGRS