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ismla 25(1):

Editorial

Aspects-based representative significance of Machine Learning algorithms & natural language processing applications in nanotechnology.

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  • @ARTICLE{10.4108/eetismla.4094,
        author={Pascal Muam Mah},
        title={Aspects-based representative significance of Machine Learning algorithms \& natural language processing applications in nanotechnology.},
        journal={EAI Endorsed Transactions on Intelligent Systems and Machine Learning},
        volume={1},
        number={1},
        publisher={EAI},
        journal_a={ISMLA},
        year={2024},
        month={12},
        keywords={Machine learning, Nanotechnology, Algorithms \& application, Natural language processing, Nanoinformatics},
        doi={10.4108/eetismla.4094}
    }
    
  • Pascal Muam Mah
    Year: 2024
    Aspects-based representative significance of Machine Learning algorithms & natural language processing applications in nanotechnology.
    ISMLA
    EAI
    DOI: 10.4108/eetismla.4094
Pascal Muam Mah1,*
  • 1: AGH University of Krakow
*Contact email: mahpascal01@gmail.com

Abstract

Introduction: The rapid changes in computational power of machine learning algorithms and natural language processing applications have led to multi-scale and many core designs in nanotechnology. Machine learning algorithms and natural language processing applications are easing the burden engineers have to go through to understand nanoparticles. Problem: There is still a challenge to predict and control particles of nanomaterials at nanoscale. Aspect-based climatic conditions are negatively impacting the world with huge modification on nanoparticles, nanomaterials and nanostructures. Objective: Study examines aspects of machine learning algorithms and natural language processing applications that can be used to predict and control particles, and structure of nanomaterials at nanoscale. Method and materials. The study examines significance of machine learning algorithms & applications in nanotechnology, examines aspects of machine learning algorithms & natural language processing applications applied in nanotechnology, and discusses current-future trends of nanotechnology based on learning algorithms & natural language processing applications. Results and conclusions. The findings result in the conclusion that machine learning & natural language processing application in nanotechnology is implementing an advanced microscopic revolution with the potential to metamorphose the world's industrialization and scale human existence. Machine learning algorithms have the potential to predict and classify nanomaterials and natural language processing has the potential to retrieve relevant data hidden within the classified nanomaterials which results has a huge significance in the pharmaceutical industry

Keywords
Machine learning, Nanotechnology, Algorithms & application, Natural language processing, Nanoinformatics
Received
2024-12-04
Accepted
2024-12-04
Published
2024-12-04
Publisher
EAI
http://dx.doi.org/10.4108/eetismla.4094

Copyright © 2024 P M Mah, licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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