Data Science and Machine Learning (Theory and Projects) A to Z - Sentiment Classification using RNN: Vocabulary Implemen

The video tutorial explains how to build a vocabulary from a data frame by counting word frequencies and applying a cutoff value to determine important words. The process involves initializing a vocabulary, counting word occurrences, and adding words that exceed the cutoff frequency. The tutorial also discusses the importance of building a vocabulary for natural language processing tasks, particularly in the context of recurrent neural networks. The implementation is demonstrated without using object-oriented programming for simplicity, and the results are tested using a CSV file.

What is the significance of using classes and object-oriented programming in vocabulary building?

How can the length of the vocabulary be checked after it has been built?

What are the potential applications of the vocabulary built from text?