An intensive masterclass on the internal mechanisms of Transformers and Large Language Models, including attention, tokenization, and scaling laws. Teaches how to build LLM components from scratch and fine-tune models for custom NLP tasks.
LEARNING_IN_PROGRESS
Learning In Progress
Instructor
Mike X Cohen
Duration
91 hours
Platform
Udemy
Status
Learning
Large language model (LLM) architectures, including GPT (OpenAI) and BERT
Transformer blocks
Attention algorithm
Pytorch
LLM pretraining
Explainable AI
Mechanistic interpretability
Machine learning
Deep learning
Principal components analysis
High-dimensional clustering
Dimension reduction
Advanced cosine similarity applications
