Feature Vectors - Understanding BERT and SBERT Transformer Models
Learn how to harness the power of feature vectors in BERT and SBERT transformer models through this educational video. Explore the process of converting text into high-dimensional vectors and tensors for use in NLP models based on transformer architecture. Master Python code implementations for vectorizers and sentence transformers, while gaining deep insights into BERT's functionality and SBERT model visualization. Follow along with practical demonstrations and code examples that showcase how to apply mathematical operations to semantic encoded vectors and compute neural network weight tensors. Delve into comprehensive explanations of transformers, complete with bonus material that breaks down BERT's inner workings and visualizes SBERT models for better understanding.