The goal of this project is to demonstrate my learning in ChatGPT prompt engineering for developers. I will be creating a collection of Jupyter Notebook files (.ipynb) to showcase different techniques and methodologies for generating high-quality text prompts that can be used for various natural language processing tasks.
This repo contains the following sections:
- Introduction to ChatGPT Prompt Engineering
- Guidelines
- Iterative Prompt Development
- Summarizing
- Inferring
- Transforming
- Expanding
- Chatbot
Each section will contain one or more .ipynb files that demonstrate different techniques and methodologies for prompt engineering.
Large Language Models (LLMs) like ChatGPT have opened up many new possibilities for natural language processing tasks. By using prompt engineering techniques, we can fine-tune these models to generate high-quality text for specific tasks. The potential applications for LLMs are vast and exciting, and there are always new things to explore and discover.
ChatGPT Prompt Engineering for Developers This repository is solely a record of my learning in ChatGPT prompt engineering for developers. All of the materials used in this project come from OpenAI and DeepLearning.AI. I hope that this repo can serve as a helpful resource for anyone interested in learning more about prompt engineering and the capabilities of large language models.
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