Categories: 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).

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"

Word Embeddings in Language Models

This post is divided into three parts; they are: • Understanding Word Embeddings • Using Pretrained Word Embeddings • Training Word2Vec with Gensim • Training Word2Vec with PyTorch • Embeddings in Transformer Models Word embeddings represent words as dense vectors in a continuous space, where semantically similar words are positioned…

June 3, 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