Chatbots for Beginners: A Complete Guide to Build Chatbots - Deep Learning-Based Chatbot Architecture and Development: V

The video tutorial explains the process of vectorizing train and test data using the function 'vectorized stories'. It covers the steps to ensure proper padding for inputs, queries, and answers, and highlights the importance of consistent padding due to varying story lengths. The tutorial also demonstrates how to tokenize specific words and previews the use of cross models and layers in the next video.

What are the outputs generated after vectorizing the training data?

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How do you ensure that the vectorization function is applied correctly to both training and test data?

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Describe the process of tokenizing the words 'yes' and 'no'.

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