prompt-engineering-note and ChatGPT-Prompt-Engineering-for-Developers

One project is a note collection related to prompt engineering, while the other is a course specifically for prompt engineering in ChatGPT; therefore, they are complementary, as the notes could supplement the course material.

Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 18/25
Maintenance 0/25
Adoption 7/25
Maturity 8/25
Community 20/25
Stars: 263
Forks: 38
Downloads: โ€”
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 25
Forks: 23
Downloads: โ€”
Commits (30d): 0
Language: Jupyter Notebook
License: โ€”
Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

About prompt-engineering-note

isLinXu/prompt-engineering-note

๐Ÿ”ฅ๐Ÿ””prompt-engineering-note๐Ÿ””๐Ÿ”ฅ

This project provides comprehensive learning notes for developers looking to master prompt engineering with Large Language Models (LLMs) like ChatGPT. It distills key principles, best practices, and practical examples for various tasks, including text summarization, sentiment analysis, language translation, and automated content generation. It's designed for software developers and AI practitioners who want to integrate and build powerful applications using OpenAI's API.

AI application development Natural Language Processing Machine Learning engineering API integration Chatbot development

About ChatGPT-Prompt-Engineering-for-Developers

Ryota-Kawamura/ChatGPT-Prompt-Engineering-for-Developers

In ChatGPT Prompt Engineering for Developers, you will learn how to use a large language model (LLM) to quickly build new and powerful applications.

This course teaches developers how to leverage large language models (LLMs) to build new applications quickly. You'll learn to input text and prompts to generate summaries, extract information, translate languages, or even draft emails. This is for software developers, AI engineers, and product managers looking to integrate AI capabilities into their products.

AI-powered application development Natural Language Processing Software engineering Product development AI integration

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