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DataCraft – AI: A Data to Insight Application Using Machine Learning
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence and Machine Learning
Abstract
This paper presents DataCraft AI, an AI-powered data-to application framework that integrates dataset ingestion, automated analysis, visualization, machine learning, and interactive application development into a unified workflow. The platform aims to simplify data science processes, reduce workflow fragmentation, and improve accessibility to data driven insights. Loan approval prediction serves as a case study, demonstrating model development, classification evaluation, and the communication of predictions and relevant features. The framework will be evaluated based on functional correctness, analytical reliability, predictive performance, and workflow efficiency. This work proposes an integrated approach to bridging automated data analytics and intelligent application development.
Keywords
Data-to-application framework, automated data analytics, machine learning, data visualization, intelligent application development, loan approval prediction, predictive analytics
References
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[3] Agal S, Katariya R. PipeBench: A benchmarking framework for end-to-end machine learning pipelines. Scientific Reports. 2026.
[4] [Authors not given]. Artificial intelligence-based and explainable AI-driven loan approval prediction system. IEEE conference publication; 2026.
[5] Gawande K, et al. An explainable ensemble learning framework for transparent and accurate loan approval prediction. Discover Artificial Intelligence. 2026.
[6] Sachan S, et al. An explainable AI decision-support system to automate loan underwriting. Expert Systems with Applications. 2020;144.
How to cite this paper
@article{1725086,
author = {Prof. Dhanush S, Mohamad Muthawakal G, Mohamed Ghouse, Gulam Hussain, Mubarak Pasha},
title = {DataCraft – AI: A Data to Insight Application Using Machine Learning},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {5},
pages = {2784-2787},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1725086.pdf},
abstract = {This paper presents DataCraft AI, an AI-powered data-to application framework that integrates dataset ingestion, automated analysis, visualization, machine learning, and interactive application development into a unified workflow. The platform aims to simplify data science processes, reduce workflow fragmentation, and improve accessibility to data driven insights. Loan approval prediction serves as a case study, demonstrating model development, classification evaluation, and the communication of predictions and relevant features. The framework will be evaluated based on functional correctness, analytical reliability, predictive performance, and workflow efficiency. This work proposes an integrated approach to bridging automated data analytics and intelligent application development.},
keywords = {Data-to-application framework, automated data analytics, machine learning, data visualization, intelligent application development, loan approval prediction, predictive analytics},
month = {November},
}