Summary
This chapter was about a real-world NLP use case for detecting fake news. In the current era of the internet, spreading fake news has become quite easy and it can be dangerous for the reputation of a person, society, organization, or political party. As we have seen in our experiments, ML classification can be used as a powerful tool for detecting fake news articles. Deep learning-based approaches can further improve the results of text classification use cases without requiring much fine-tuning data.
After reading this chapter, you should be confident about training and applying classification models on text classification use cases, similar to fake news detection. You should also have a good understanding of the cleaning and pre-processing steps that are needed to apply classical models, such as random forest, on text data. At this point, you should be able to launch large-scale ML experiments as Vertex AI training jobs. Finally, you should have a good understanding of...
