Large Language Models (LLM) Concepts - Interview Questions and Answers
In this post, I explain What is LLM?, Language Modeling Basics, Tokenization & Words in LLMs, Neural Network Foundations, Transformer Architecture, Scaling: Parameters, FLOPs, Emergent Abilities, Architectural Variants, Training Paradigms, Sampling & Decoding Techniques, In-context Learning & Prompting, Hallucinations, Bias & Reliability, Explainability & Interpretability, Retrieval-Augmented Generation RAG, Multimodality & Multimodal LLMs MLLMs, and Domain-Specialization & Fine-tuning. If you want my complete Large Language Models (LLM) Concepts document that additionally explains the following topics, please message me on LinkedIn : Top Models Overview (GPT-series, BERT family, PaLM, LLaMA, Claude, Gemini), Prompt Engineering Strategies, LLM Usage Patterns, Best Practices for Reliability, Efficiency Optimization and Integration & Tooling Question : What is a Large Language Model (LLM)? Answer : A Large Language Model (LLM) is a type of neural network...