In recent years, machine learning models that can comprehend and respond to human language have advanced significantly thanks to natural language processing (NLP). As these models have advanced, a variety of applications, including chatbots, virtual assistants, machine translation, and sentiment analysis, have been made possible. These models, however, rely on prompts to give context and direction for the intended result. To make sure the model produces accurate and pertinent responses, prompt engineering entails creating high-quality prompts.
Prompt Engineering: The ultimate guide (free)
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