Labeling Data for Classification

In this chapter, we are going to learn how to label tabular data by applying business rules programmatically with Python libraries. In real-world use cases , not all of our data will have labels. But we need to prepare labeled data for training the machine learning models and fine-tuning the foundation models. The manual labeling of large sets of data or documents is cumbersome and expensive. In case of manual labeling, individual labels are created one by one. Also, occasionally, sharing private data with a crowd-sourcing team outside the organization is not secure.

So, programmatically labeling data is required to automate data labeling and quickly label a large-scale dataset. In case of programmatic labeling, there are mainly three approaches. In the first approach, users create labeling functions and apply to vast amounts of unlabeled data to auto label large training datasets. In the second approach, users apply semi-supervised learning to create...