Transformers & Attention (Overview)

Summary

The architecture behind virtually all modern NLP and LLMs — the attention mechanism lets a model weigh the relevance of every other word when processing each word, capturing context far better than RNNs.

How to Learn This

1Read a beginner-friendly visual explainer of the attention mechanism.
2Learn why Transformers can be trained in parallel, unlike sequential RNNs.
3Understand this architecture is the foundation for models like BERT and GPT.

Sequence Models for NLP

Pretrained LLMs & Fine-Tuning Basics

More topics in NLP & Modern AI

Text Preprocessing (Tokenization, Stemming, Lemmatization)Bag of Words & TF-IDF Word Embeddings (Word2Vec, GloVe)Sequence Models for NLP Pretrained LLMs & Fine-Tuning Basics Prompt Engineering for Data Tasks

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