A Platform to Help in Generating Code for Machine Learning and Data Science Projects

Rajiv, Charles Samuel; K, Parkavi

doi:10.2139/ssrn.4033072

Cited by 3 publications

(2 citation statements)

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“…The architecture is structured using FastAPI, Laravel, and MariaDB. FastAPI was chosen due to its superior performance compared to NodeJS and Go [17].…”

Section: Implementation Phasementioning

confidence: 99%

Implementation of Cosine Similarity Algorithm on Omnibus Law Drafting

Syam,

et al. 2024

IJACSA

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Drafting of Omnibus Laws presents a complex challenge in legal governance, often involving the integration and consolidation of disparate legal provisions into a unified framework. In this context, the application of advanced computational techniques becomes crucial for streamlining the drafting process and ensuring coherence across the law's various components. Cosine similarity, a widely used measure in natural language processing and document analysis, offers a quantitative means to assess the similarity between different sections or articles within the Omnibus Law draft. By representing legal texts as high-dimensional vectors in a vector space model, cosine similarity enables the comparison of textual similarity based on the cosine of the angle between these vectors. Implementing cosine similarity in the context of omnibus law using FastAPI and Laravel can be a valuable tool for analyzing similarity between legal documents, especially in the context of omnibus law. Legal practitioners and researchers can use the cosine similarity measure to compare the textual content of different legal documents and identify similarities. This can aid in tasks such as legal document retrieval, clustering similar provisions, and detecting potential inconsistencies. The combination of FastAPI and Laravel provides a potent and efficient way to develop and deploy this functionality, contributing to the advancement of legal informatics and analysis. The dataset used is Undang-Undang (UU) which used Bahasa from 1945 to 2022, comprising a total of 1705 UU. The implemented cosine similarity yielded a recall rate of 90.10% on the law.

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“…The architecture is structured using FastAPI, Laravel, and MariaDB. FastAPI was chosen due to its superior performance compared to NodeJS and Go [17].…”

Section: Implementation Phasementioning

confidence: 99%

Implementation of Cosine Similarity Algorithm on Omnibus Law Drafting

Syam,

et al. 2024

IJACSA

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show abstract

“…FastAPI merupakan didesain agar mudah untuk digunakan, selain itu FastAPI juga didesain mirip dengan framework Flask yang merupakan salah satu framework yang banyak digunakan (Azhari, 2022). FastAPI juga merupakan salah satu framework tercepat dalam bahasa pemrograman Python dan setara dengan NodeJS dan Go (Rajiv, 2022). FastAPI juga telah banyak digunakan dalam membangun RESTful API untuk mengimplementasikan berbagai model machine learning seperti misalnya dalam hal monitoring gempa (Zhu dkk., 2022).…”

Section: Hasil Dan Pembahasanunclassified

Pengembangan Restful Api Untuk Model Machine Learning Indoor-Outdoor Dalam Aplikasi Peminjaman Ruangan

Arvanchrist Charlie Wijaya,

I Gede Arta Wibawa,

I Dewa Made Bayu Atmaja Darmawan

2022

JUPITA

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Pada jaman digital ini kini berbagai aktivitas dan kerja dapat dipermudah dengan penggunaan teknologi informasi seperti misalnya dalam hal peminjaman ruangan. Peminjaman ruangan secara konvensional ternilai kurang efisien, oleh karena itu CV. Avatar Solution memberikan solusi terkait permasalahan tersebut dengan pengembangan aplikasi peminjaman ruangan. Dalam proses pengembangannya terdapat pula berbagai bidang informatika yang dapat mendukung dalam seperti bidang machine learning. Dari model yang dikembangkan dari bidang machine learning tidak dapat diimplementasikan secara langsung. Sehingga perlu untuk dilakukan proses untuk diintegrasikan dengan aplikasi. Dalam integrasi model dengan aplikasi dibuatkan RESTful API yang bertujuan supaya model machine learning dapat digunakan dalam aplikasi peminjaman ruangan.

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Video Based Fashion Recommendation System

Mukherjee,

2023

2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)

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A Platform to Help in Generating Code for Machine Learning and Data Science Projects

Cited by 3 publications

References 0 publications

Implementation of Cosine Similarity Algorithm on Omnibus Law Drafting

Implementation of Cosine Similarity Algorithm on Omnibus Law Drafting

Pengembangan Restful Api Untuk Model Machine Learning Indoor-Outdoor Dalam Aplikasi Peminjaman Ruangan

Video Based Fashion Recommendation System

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