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Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks
This paper compares the usability of various Apple MacBook Pro laptops were tested for basic machine learning research applications, including text-based, vision-based, and tabular data. Four tests/benchmarks were conducted using four different MacBook Pro models—M1, M1 Pro, M2, and M2 Pro. A script...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10305298/ https://www.ncbi.nlm.nih.gov/pubmed/37420589 http://dx.doi.org/10.3390/s23125424 |
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author | Kasperek, David Antonowicz, Pawel Baranowski, Marek Sokolowska, Marta Podpora, Michal |
author_facet | Kasperek, David Antonowicz, Pawel Baranowski, Marek Sokolowska, Marta Podpora, Michal |
author_sort | Kasperek, David |
collection | PubMed |
description | This paper compares the usability of various Apple MacBook Pro laptops were tested for basic machine learning research applications, including text-based, vision-based, and tabular data. Four tests/benchmarks were conducted using four different MacBook Pro models—M1, M1 Pro, M2, and M2 Pro. A script written in Swift was used to train and evaluate four machine learning models using the Create ML framework, and the process was repeated three times. The script also measured performance metrics, including time results. The results were presented in tables, allowing for a comparison of the performance of each device and the impact of their hardware architectures. |
format | Online Article Text |
id | pubmed-10305298 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103052982023-06-29 Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks Kasperek, David Antonowicz, Pawel Baranowski, Marek Sokolowska, Marta Podpora, Michal Sensors (Basel) Article This paper compares the usability of various Apple MacBook Pro laptops were tested for basic machine learning research applications, including text-based, vision-based, and tabular data. Four tests/benchmarks were conducted using four different MacBook Pro models—M1, M1 Pro, M2, and M2 Pro. A script written in Swift was used to train and evaluate four machine learning models using the Create ML framework, and the process was repeated three times. The script also measured performance metrics, including time results. The results were presented in tables, allowing for a comparison of the performance of each device and the impact of their hardware architectures. MDPI 2023-06-08 /pmc/articles/PMC10305298/ /pubmed/37420589 http://dx.doi.org/10.3390/s23125424 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kasperek, David Antonowicz, Pawel Baranowski, Marek Sokolowska, Marta Podpora, Michal Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks |
title | Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks |
title_full | Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks |
title_fullStr | Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks |
title_full_unstemmed | Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks |
title_short | Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks |
title_sort | comparison of the usability of apple m2 and m1 processors for various machine learning tasks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10305298/ https://www.ncbi.nlm.nih.gov/pubmed/37420589 http://dx.doi.org/10.3390/s23125424 |
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