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In this study, we introduce JarviX, a sophisticated data analytics framework.JarviX is designed to employ Large Language Models (LLMs) to facilitate anautomated guide and execute high-precision data analyzes on tabular datasets.This framework emphasizes the significance of varying column types,capitalizing on state-of-the-art LLMs to generate concise data insightsummaries, propose relevant analysis inquiries, visualize data effectively, andprovide comprehensive explanations for results drawn from an extensive dataanalysis pipeline. Moreover, JarviX incorporates an automated machine learning(AutoML) pipeline for predictive modeling. This integration forms acomprehensive and automated optimization cycle, which proves particularlyadvantageous for optimizing machine configuration. The efficacy andadaptability of JarviX are substantiated through a series of practical use casestudies.

JarviX: A LLM No code Platform for Tabular Data Analysis and Optimization