7 Advanced Feature Engineering Tricks Using LLM Embeddings

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7 Advanced Feature Engineering Tricks for Text Data Using LLM Embeddings

Large language models (LLMs) are not only good at understanding and generating text; they can also turn raw text into numerical representations called embeddings.

October 30, 2025

In "AI/ML Research"

Feature Engineering with LLM Embeddings: Enhancing Scikit-learn Models

Large language model embeddings, or LLM embeddings, are a powerful approach to capturing semantically rich information in text and utilizing it to leverage other machine learning models — like those trained using Scikit-learn — in tasks that require deep contextual understanding of text, such as intent recognition or sentiment analysis.

July 18, 2025

In "AI/ML Research"

Word Embeddings for Tabular Data Feature Engineering

It would be difficult to argue that word embeddings — dense vector representations of words — have not dramatically revolutionized the field of natural language processing (NLP) by quantitatively capturing semantic relationships between words.

July 12, 2025

In "AI/ML Research"

AI Generated Robotic Content