Prompt-Engineering

This document explores advanced prompt engineering methods including zero-shot, few-shot, chain-of-thought, and self-consistency techniques, along with practical tools and applications for effective LLM interactions.

This document introduces in-context learning and prompt engineering explaining how LLMs can learn new tasks from examples provided in prompts without additional training, along with techniques for crafting effective prompts to guide AI systems.

Two key principles for writing effective prompts for large language models to help generate accurate and relevant responses

Overview of the three main types of Large Language Models (LLMs) based on their training and functionality, including characteristics and use cases