Bert
term_id: bert
Category: basic_concepts
Definition
BERT is a transformer-based machine learning technique for NLP pre-training developed by Google. It uses masked language modeling and next sentence prediction to learn bidirectional representations from text. This allows BERT to understand context from both left and right directions simultaneously, significantly improving performance on tasks like question answering and sentiment analysis compared to unidirectional models.
Summary
Bidirectional Encoder Representations from Transformers is a pre-trained natural language processing model.
Key Concepts
- Transformer Architecture
- Masked Language Modeling
- Pre-training
- Fine-tuning
Use Cases
- Question Answering Systems
- Sentiment Analysis
- Text Classification