#LLMs
11 articles tagged with #LLMs
How ChatGPT Works: Explained Simply
A comprehensive guide to how chatgpt works: explained simply — written for learners at every level.
Claude vs ChatGPT vs Gemini: Which Is Best?
A comprehensive guide to claude vs chatgpt vs gemini: which is best? — written for learners at every level.
Large Language Models (LLMs) Explained for Beginners
An LLM predicts the next piece of text, one token at a time — this guide explains how ChatGPT, Claude, and Gemini actually work.
20 ChatGPT Prompts to Boost Your Productivity
Great prompts share four parts: role, task, context, and format — here are 20 ready-to-use prompts for daily work.
Prompt Engineering: Get Better Results from Any LLM
The difference between a mediocre AI output and an excellent one is usually the prompt. This guide covers the techniques that consistently produce better results: clarity, context, examples, chain-of-thought, system prompts, and output formatting — with real before/after examples.
RAG Explained: Retrieval-Augmented Generation
RAG is how you give an LLM access to your own private data without training a new model. This guide explains the full pipeline — chunking, embeddings, vector search, and augmented generation — with a working Python example using open-source tools.
Fine-Tuning LLMs: A Practical Guide
Fine-tuning lets you adapt a pre-trained language model to your specific domain, style, or task — without training from scratch. This guide explains when fine-tuning is the right choice, how LoRA makes it affordable, and how to run a fine-tuning job with Hugging Face PEFT.
Vibe Coding: How to Build Faster with AI Without Losing Control
AI coding tools have shifted from autocomplete to full code generation, multi-file refactoring, and autonomous debugging. This guide explains how to use tools like Copilot, Cursor, and Claude Code effectively — including the critical skill of reviewing AI-generated code before shipping it.
Async Python: asyncio Explained for Beginners
Async Python lets a single thread handle hundreds of concurrent I/O operations — making it essential for web APIs, database calls, and AI integrations. This guide explains coroutines, the event loop, await, gather, and real patterns you'll use in FastAPI, httpx, and LLM streaming.
Building Your First AI-Powered App with the Anthropic API
The fastest way to understand AI engineering is to build something real. This project- based guide walks you through building a writing assistant powered by Claude — from your first API call through streaming responses, a FastAPI backend, a simple frontend, and deployment.
How Large Language Models Actually Work
LLMs seem magical until you understand what they are: next-token predictors trained on massive text corpora. This guide explains tokenisation, embeddings, the transformer architecture, attention mechanism, and how training works — without requiring a maths degree.