NLP and Large Language Models
"Teaching machines to understand language"
NLP Basics: Tokenization and Preprocessing
Chopping vegetables before cooking, prepping text before training
Word Embeddings and Word2Vec
Placing words on a map where similar words live close together
BERT: Bidirectional Understanding
Reading a sentence from both ends to understand context better
GPT: Predicting the Next Word
The most sophisticated autocomplete ever built
Fine-tuning Pretrained Models
Taking a chef trained on French cuisine and teaching them Italian food
Prompt Engineering
Knowing exactly how to ask a question to get the best answer
RAG: Retrieval Augmented Generation
A student allowed to bring notes to an exam: the AI retrieves context before answering
Vector Databases
A library organized by meaning, not alphabetically
Why LLMs Hallucinate
A confident person making things up because they do not know what they do not know
Build a Mini Chatbot with RAG
Put it all together