BERT (Bidirectional Encoder Representations from Transformers) is a deep learning model introduced by Google in 2018 that processes text bidirectionally to understand context. It uses two training techniques: Masked Language Model (MLM), which predicts randomly masked words, and Next Sentence Prediction (NSP), which determines
Table of contents
What is BERT?What is the difference between BERT and Transformer?What is BERT used for?How does BERT work?Fine-tuning BERTBERT variationsWhat do BERT and GPT have in common?What is the difference between BERT and GPT?ConclusionSort: