Data Science and Machine Learning (Theory and Projects) A to Z - RNN Implementation: Language Modelling Next Word Predic

The video tutorial explains the concept of vocabulary in language models, focusing on indexing unique words. It provides examples of how words are indexed and used to predict subsequent words in a sequence. The tutorial also covers the creation of input and target vectors for training models and introduces the concept of converting indices into feature vectors for computation, leading to word embeddings.

Describe the process of converting indices to feature vectors.

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What is the significance of embeddings in the context of vocabulary representation?

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