Bridging the Gap for Non-Programmers with No-Code ML Solutions

This paper presents ‘No-Code ML’, a web-based platform designed to democratize access to machine learning (ML) technologies for non-programmers. Traditional ML development often requires significant programming expertise, limiting its accessibility to a broader audience. However, with the emergence of no-code ML platforms, individuals without coding backgrounds can now leverage the power of ML algorithms for various applications. No Code ML bridges this gap by offering an intuitive interface and a diverse set of ML tools, enabling users to build, deploy, and manage ML models without writing a single line of code. By highlighting the capabilities and benefits of No-Code ML, this paper contributes to the ongoing discourse on democratizing ML and empowers a wider audience to harness the transformative potential of artificial intelligence.

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Publication Details

Published
2025-02-07
DOI
https://doi.org/10.1109/etis64005.2025.10961566
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
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Bridging the Gap for Non-Programmers with No-Code ML Solutions

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Parallel Computing and Optimization Techniques
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Bridging the Gap for Non-Programmers with No-Code ML Solutions

Jacob Thomas, Jayasankar Shyam, Cyril K Sony, Aswin Jeev Johny, Basil Siby
article en

Abstract

This paper presents ‘No-Code ML’, a web-based platform designed to democratize access to machine learning (ML) technologies for non-programmers. Traditional ML development often requires significant programming expertise, limiting its accessibility to a broader audience. However, with the emergence of no-code ML platforms, individuals without coding backgrounds can now leverage the power of ML algorithms for various applications. No Code ML bridges this gap by offering an intuitive interface and a diverse set of ML tools, enabling users to build, deploy, and manage ML models without writing a single line of code. By highlighting the capabilities and benefits of No-Code ML, this paper contributes to the ongoing discourse on democratizing ML and empowers a wider audience to harness the transformative potential of artificial intelligence.

Government Medical College (IN)
Openalex Percentile: Top 93%
Parallel Computing and Optimization Techniques
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