veekaybee/what_are_embeddings resource

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1096 stars · 86 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A survey paper and accompanying Jupyter notebooks by Vicki Boykis providing a deep dive into embeddings, from TF-IDF and Word2Vec through transformer-based representations. It includes the LaTeX source, a generated website, and complementary notebook code.

Use cases

• understand what embeddings are from first principles
• learn the history of word and text representations like TF-IDF and Word2Vec
• get a conceptual foundation before working with transformer models
• find a generalist introduction to embeddings for recommendation systems
• study notebook examples of embedding techniques
• cite a reference on embeddings in industrial ML systems

When to choose

• you want a conceptual, fundamentals-first explanation of embeddings
• you're a generalist or engineer needing background before deep learning work
• you want runnable notebooks alongside the reading material

When to avoid

• you need a production embedding library or API
• you want cutting-edge research papers rather than a survey
• you need a maintained software tool with tests and CI

Facets

learning-resource · maturity stable

nlp machine-learning documentation machine-learning deep-learning tutorials python embeddings survey-paper educational jupyter-notebooks latex natural-language-processing

Member repositories

For agents

markdown · JSON · MCP: product_card(name="veekaybee/what_are_embeddings")