A Gentle Introduction to Word Embedding and Text Vectorization
“I’m feeling blue today” versus “I painted the fence blue. Source link
“I’m feeling blue today” versus “I painted the fence blue. Source link
This article is divided into three parts; they are: • Full Transformer Models: Encoder-Decoder Architecture • Encoder-Only Models • Decoder-Only Models The original transformer architecture, introduced in “Attention is All You Need,” combines an encoder and decoder specifically designed for…
Learning machine learning can be challenging. Source link
In machine learning model development, feature engineering plays a crucial role since real-world data often comes with noise, missing values, skewed distributions, and even inconsistent formats. Source link
Machine learning model development often feels like navigating a maze, exciting but filled with twists, dead ends, and time sinks. Source link
This post is divided into five parts; they are: • Naive Tokenization • Stemming and Lemmatization • Byte-Pair Encoding (BPE) • WordPiece • SentencePiece and Unigram The simplest form of tokenization splits text into tokens based on whitespace. Source link