# GloVe + FastText: Global Co-Occurrence Matrix + Subword N-Gram Extension

> Source: https://sukruyusufkaya.com/en/learn/llm-muhendisligi/glove-fasttext-global-cooccurrence-subword-extension
> Updated: 2026-05-13T13:00:27.105Z
> Category: LLM Mühendisliği
> Module: Module 7: Embedding Layer — The Vector Space of Meaning
**TLDR:** GloVe (Pennington 2014) global co-occurrence matrix approach vs Word2Vec local window: mathematical formulation, weighted least squares objective, X_ij interpretation. FastText (Bojanowski 2017) subword n-gram embedding: 'merhaba' = 'mer' + 'erh' + ... OOV problem solution, ideal for Turkish morphological languages. Performance comparison, which scenario for each.