Text Embeddings

• is a type of embedding in the domain of text
• machine learning models take requires numbers or numbers as input. When working with text, the first thing you must do is come up with a strategy to convert strings to numbers (or to “vectorize” the text) before feeding it to the model
• used to transform text features extracted from Information Extraction/NLP into numbers (or vectors)

Text Embedding - Types

• Word Embeddings
• Sentence Embeddings
• Paragraph Embeddings
• Document Embeddings

Text Embedding - Strategies/Methods

• Bag of Words (BoW)
• Term-Frequency Inverse-Document-Frequency (TF-IDF) Term Frequency - Inverse Document Frequency