Categories: AI/ML Research

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.

Why and When to Use Sentence Embeddings Over Word Embeddings

Choosing the right text representation is a critical first step in any natural language processing (NLP) project.

September 27, 2025

In "AI/ML Research"

10 Ways to Use Embeddings for Tabular ML Tasks

Embeddings — vector-based numerical representations of typically unstructured data like text — have been primarily popularized in the field of natural language processing (NLP).

January 13, 2026

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"

AI Generated Robotic Content