BERT explained: Training, Inference, BERT vs GPT/LLamA, Fine tuning, [CLS] token
58:04
Attention is all you need (Transformer) - Model explanation (including math), Inference and Training
1:10:55
LLaMA explained: KV-Cache, Rotary Positional Embedding, RMS Norm, Grouped Query Attention, SwiGLU
23:24
Fine-Tuning BERT for Text Classification (Python Code)
28:18
Fine-tuning Large Language Models (LLMs) | w/ Example Code
1:10:21
Insights into Your NLP Engine with NLP-as & Retrieval with Haystack
27:14
Transformers (how LLMs work) explained visually | DL5
49:24
Retrieval Augmented Generation (RAG) Explained: Embedding, Sentence BERT, Vector Database (HNSW)
1:52:27