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ChatGPT for Text Classification
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In this comprehensive tutorial, we dive into the world of Natural Language Processing (NLP), Machine Learning, and Data Science to build a robust toxic comment classifier using ChatGPT and deploy it with FastAPI. Learn step-by-step how to connect to OpenAI's API with Python, optimize your prompts for maximum accuracy, and seamlessly deploy your model for real-world applications.
🔍 Key Topics Covered:
1. OpenAI API Connection: Explore how to connect to OpenAI's API using Python to leverage ChatGPT for text classification.
2. Prompt Engineering Techniques: Discover essential prompt engineering techniques for achieving optimal classification accuracy, including the use of delimiters, structured output formats like JSON, and providing the model with time to think through techniques like "chain of thought."
3. FastAPI Deployment: Learn the ins and outs of deploying your toxic comment classifier with FastAPI.
🔑 TIMESTAMPS
================================
0:00 - Introduction
1:54- OpenAI API connection
2:39 - Text Classifier with Prompt Engineering
8:30- Deploy with Fast API
🔍 Key Topics Covered:
1. OpenAI API Connection: Explore how to connect to OpenAI's API using Python to leverage ChatGPT for text classification.
2. Prompt Engineering Techniques: Discover essential prompt engineering techniques for achieving optimal classification accuracy, including the use of delimiters, structured output formats like JSON, and providing the model with time to think through techniques like "chain of thought."
3. FastAPI Deployment: Learn the ins and outs of deploying your toxic comment classifier with FastAPI.
🔑 TIMESTAMPS
================================
0:00 - Introduction
1:54- OpenAI API connection
2:39 - Text Classifier with Prompt Engineering
8:30- Deploy with Fast API
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