Advanced Chatbots with Deep Learning and Python - Vectorizing Train and Test Data

The video tutorial explains the process of vectorizing train and test data using a function called 'vectorized stories'. It covers the outputs of vectorization, including padding for stories, questions, and answers. The tutorial also discusses the similarities in padding between train and test data due to the use of maximum story length. It explains the presence of zeros in the data and introduces tokenization of specific words. The video concludes with a preview of using cross models and layers in the next tutorial.

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