Understanding Vector Embeddings: How Machines Learn Semantic Meaning

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In the rapidly evolving world of artificial intelligence (AI) and natural language processing (NLP), one of the most groundbreaking concepts enabling machines to understand language is vector embeddings. By converting words, sentences, and even images into numerical representations, vector embeddings allow machines to capture semantic meaning and context in a way that traditional algorithms could … Read more

BERT Explained with Example: A Complete Guide with Theory and Tutorial

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Introduction Natural Language Processing (NLP) has evolved rapidly over the last decade, and at the forefront of this revolution stands BERT (Bidirectional Encoder Representations from Transformers)—a groundbreaking language model introduced by Google AI in 2018. 1. What is BERT? BERT stands for Bidirectional Encoder Representations from Transformers. It is a deep learning model based on … Read more