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Have you ever wondered how to make a chatbot more conversational, a text generator more creative, or an image creator more realistic? If so, you might be interested in learning about prompt engineering, a new and exciting field that combines machine learning, natural language processing, and human creativity. Prompt engineering is the art and science of designing inputs that elicit the desired outputs from large language models (LLMs), such as ChatGPT, GPT-3, DALL-E, Stable Diffusion, Midjourney, and others. These models are trained on massive amounts of text, code, or images, and can generate amazing content based on a given prompt. However, they also have their limitations and challenges, such as a lack of common sense, logical reasoning, or domain knowledge. That’s where prompt engineering comes in. Prompt engineering involves crafting specific and clear prompts to guide the model toward the intended goal while also being general enough to capture the full range of relevant information. Prompt engineering also requires understanding the context and purpose of the task or application for which the model is being used, and providing external data or documents if needed. In this video, we will introduce you to the key concepts and use cases of prompt engineering, such as: How to structure and organize your prompts How to use parameters and modifiers to fine-tune your prompts How to leverage existing templates and examples How to evaluate and improve your prompts How to become a prompt engineer By the end of this video, you will have a better understanding of what prompt engineering is, how it works, and why it matters. You will also learn some tips and tricks to create your own prompts and explore the amazing possibilities of generative AI. If you are ready to dive into the world of prompt engineering, then stay tuned and enjoy the video! More @https://learn.deeplearning.ai Full Course : https://www.youtube.com/playlist?list=PL-Sya592UvbeBc_7I7_jYlYaJqgGSeqnw Channel Link : https://youtube.com/@wondboi?sub_confirmation=1
