Llmnotes

Create a comprehensive, structured learning resource repository focused on Deep Learning, specifically covering Transformer models and Reinforcement Learning. The structure should organize notes into distinct sections for both topics. For Transformers, include parts covering foundational theory, core components like Tokenizer and RoPE, attention mechanisms, MoE, training aspects, evaluation, and deployment. For Reinforcement Learning, cover foundational concepts, value-based methods, policy-based methods, model-based/MARL, and LLM alignment techniques. Include a build script example that compiles these notes into separate PDF files for both Transformers and RL.