Deep-Learning

Explore how attention mechanisms allow neural networks to focus on relevant information, enabling breakthroughs in NLP and beyond.

BERT is a transformer-based language model that revolutionized NLP by learning bidirectional context. This guide covers its architecture, pre-training objectives, fine-tuning strategies, and variants.

Learn about the essential non-linear functions that power neural networks, from classical Sigmoid to modern GELU used in Transformers.

Understand the Transformer architecture that revolutionized NLP and now powers GPT, BERT, and all modern large language models.