Data Science and Machine Learning (Theory and Projects) A to Z - RNN Architecture: ManyToMany Model Solution 01

The video tutorial introduces named entity recognition (NER) in natural language processing (NLP), explaining how sentences are analyzed to classify words into predefined categories such as location, person, organization, time, and date. It discusses the process of labeling each word with a category and the relationship between word embeddings and labels. The tutorial also covers the many-to-many architecture, where inputs and labels have the same length, though different inputs may vary in length.

What does it mean for a sentence to have an equal number of labels?

Describe the many-to-many architecture mentioned in the context of named entity recognition.