EP 39 | CME295 in 15 Minutes (The Full Recap)

Short on time? We’ve distilled the entire Stanford CME295 course into a single, high-energy video recap. This "Cram Session" takes you on a complete journey from the absolute basics of natural language processing to the cutting edge of Large Language Models.Watch or listen for the "Best Of" our course deep dives:The Foundation: Moving past RNNs into the Self-Attention revolution and the core Transformer architecture.The Training Pipeline: The massive undertaking of Pre-training, Supervised Fine-Tuning (SFT), and Preference Tuning to build a safe assistant.Reasoning & Agents: How models use Chain of Thought to solve multi-step problems , and how RAG and Tool Calling turn them into autonomous agents.The Future: A look at what's next, including Vision Transformers (ViT), Diffusion LLMs, and highly capable Small Language Models (SLMs).Note: This is an AI-generated study resource created via NotebookLM based on the Stanford CME295 curriculum and personal study notes.