Diane Khambu·Sep 12Word Vectorization and Embeddings with the Skip-Gram ModelIt’s kind of intriguing to see words represented as numbers. What if I told you those digits are just indices of a lookup table in a…
AI & Data Science 604·Jul 5Exploring Word Embedding Techniques Part2: Meaning As Vectors, Word2Vec and GloVe.Advanced embedding systems to help computers understand complex language patterns and word similarities much better.
Feliks VP Samosir·May 24Dari Hitungan ke Prediksi: Bagaimana Mesin Belajar Memahami Hubungan AntarkataIni adalah bagian kedua dari seri catatan belajar saya atas video perkuliahan dari CS224N (Stanford University) dan CMU 11–737 (Carnegie…
Siddhesh Inamdar·Jan 7The Day We Stopped Counting Words: A Look at Semantic AlchemyImagine trying to learn a language by reading a dictionary, but the definitions are missing. You only know that “dog” appears on page 45…
AmeerSaleem·Jan 4Intro to word embeddings with word2vec, CBOW and Skip-gramExploring how computers can store words in vector form, and how word2vec allows for the construction of meaningful word embeddings.
Rashmi S·Dec 3, 2025Word2vec: Understanding the Revolution in Word EmbeddingsWord2vec is a highly influential technique in natural language processing (NLP) used for generating word embeddings. Word embeddings are…
Satvik Tejas·Jul 6, 2025Debunking the Input Layer Myth in Word2Vec: A Deep Dive into Embedding LearningMany tutorials mislead us into believing Word2Vec uses one-hot input fed into a neural network. But that’s inefficient and fundamentally…
Nirashanelki·Jan 18, 2025Word2Vec — Skip Gram ModelsIn the previous article, we just discovered Word2Vec. Now, let’s dive into the details and learn how the skip-gram models work.
