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Explore a comparative analysis of Large Language Models (LLMs) and XGBoost for tabular data classification in this 11-minute conference talk by Sebastian Cattes. Discover the potential of fine-tuned LLMs as an alternative to traditional machine learning algorithms for tabular datasets. Learn about the process of translating tabular data into natural language for LLM fine-tuning and examine the performance results of LLM-based predictions versus XGBoost. Gain insights from Sebastian's extensive experience as a Senior Data Scientist and Team Lead, who has developed multiple products and proofs of concept in retail and manufacturing using cloud solutions.
Syllabus
LLM XGBoost - Can a Fine-Tuned LLM Beat XGBoost on Tabular Data? // Sebastian Cattes // LLMs Part 2
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