Developing Interactive Machine Learning Applications: A React-Based Frontend and a Microservices-Based Backend
Integrating a microservices backend with a front end implemented with React is a scalable performancedriven solution to designing interactive applications of machine learning (ML). Traditional monolithic systems fall short of the requirements of scalability, modularity, and real-time processing capa...
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| Published in: | International journal of innovative research in science, engineering and technology Vol. 13; no. 7 |
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| Main Author: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
30.07.2024
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| ISSN: | 2319-8753, 2319-8753 |
| Online Access: | Get full text |
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| Summary: | Integrating a microservices backend with a front end implemented with React is a scalable performancedriven solution to designing interactive applications of machine learning (ML). Traditional monolithic systems fall short of the requirements of scalability, modularity, and real-time processing capabilities, rendering them inefficient in supporting systems with the capabilities of ML. A microservices backend adds strength to the system by providing independent deployment and scalability of models with optimal performance while providing real-time interaction with the user through the user interface of React.js. API-driven interactions between the backend microservices and the backend, state management by the state management architecture of React.js, and containerized microservices are the significant components that add to the optimal interaction of the backend with the front end to build scalable and interactive applications of ML with the optimal performance possible. |
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| ISSN: | 2319-8753 2319-8753 |
| DOI: | 10.15680/IJIRSET.2024.1307184 |