Summary
In this chapter, we delved into the realm of text data exploration using Python, gaining a comprehensive understanding of harnessing Generative AI and OpenAI models for effective text data labeling. Through code examples, we explored diverse text data labeling tasks, including classification, summarization, and sentiment analysis.
We then extended our knowledge by exploring Snorkel labeling functions, allowing us to label text data with enhanced flexibility. Additionally, we delved into the application of K-means clustering for labeling text data and concluded by discovering how to label customer reviews using neural networks.
With these acquired skills, you now possess the tools to unlock the full potential of your text data, extracting valuable insights for various applications. The next chapter awaits, where we will shift our focus to video data exploration, exploring different methods to gain insights from this dynamic data type.
