Introduction TF-IDF (Term Frequency-Inverse Document Frequency) is a statistical measure used to evaluate the importance of a word in a document relative to a collection of documents (corpus). It combines two metrics: Term Frequency (TF) and Inverse Document Frequency (IDF). The TF-IDF value increases proportionally with the number of times a word appears in the … Read more
Introduction Embeddings are numerical representations of concepts converted to number sequences, which make it easy for computers to understand the relationships between those concepts. Whether it’s natural language processing, computer vision, recommender systems, or other applications, embeddings play a crucial role in enhancing model performance and scalability. Text embeddings measure the relatedness of text strings. … Read more
