Fourth Industrial Revolution

In this post, I explain Introduction to RAG in LLMs (Large Language Models), RAG Concepts in LLMs, Retrieval Modules and Vector Embeddings, Indexing Strategies and Vector Databases, Document Ingestion and Preprocessing, RAG in LLM Python, RAG Frameworks (such as LangChain and LlamaIndex), Retrieve‑Then‑Generate vs Generate‑Then‑Retrieve, Prompt Engineering for RAG and Evaluation Metrics for RAG. You can test your knowledge of LLMs in Python by attempting the Quiz after every set of Questions and Answers. If you want my complete Retrieval-Augmented Generation (RAG) Framework in LLMs document that additionally includes the following important topics, you can message me on LinkedIn : Optimization and Caching, Advanced RAG Techniques (such as RAG multimodal retrieval), RAG in LLamaIndex Example with code, Best Practices and Troubleshooting RAG and RAG in LLM consolidated Quiz with multiple‑choice questions and answers to test your knowledge. Question : What does RAG stand for in...

In this post, I explain LLMs in Python, Python Setup & Installation, Inference with Transformers, Calling ChatGPT API in Python, Python Local Deployment with Hugging Face Models, Prompt Engineering in Python and FineTuning & Custom Training (including LoRA). You can test your knowledge of LLMs in Python by attempting the Quiz after every set of Questions and Answers. If you want my complete Introduction to LLMs in Python document that additionally includes the following important topics, you can message me on LinkedIn : Python Advanced Techniques (Streaming, Batching & Callbacks), Python Efficiency & #Optimization (quantization, distillation, and parameter‑efficient tuning), Integration & Deployment Workflows, LLMs in Python Best Practices & Troubleshooting, and consolidated Introduction to LLMs in Python Quiz (with answer explanations to reinforce learning). Question : What do I mean by "Introduction to LLMs in Python"? Answer : Introduction to LL...

In this post, I explain Introduction to Generative AI with Large Language Models, Key Concepts & Definitions, Underlying Models: Transformers & Beyond, Modeling andTraining Foundations, Sampling & Decoding for Generation Quality, Prompting Strategies for Generative AI (zero-shot, few-shot, chain-of-thought prompting, role prompting, and advanced prompt tactics), Scaling & Emergent Capabilities in Generation, Mitigating Hallucination & Ensuring Output Reliability -RAG and grounding, and Advanced Generation: Multimodality & Specialized Content. If you want my full Gen AI with LLMs document also including the following topics, you can use the Contact Form (in the right pane) or message me in LinkedIn: Popular Generative LLMs & Frameworks (GPT-series, Claude, PaLM, Gemini, LLaMA), Efficiency & Deployment Optimization distillation, quantization, parameter-efficient tuning etc.), Ethics, Privacy & Governance, Generative AI Project Workflow (end-to-end li...