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

The video tutorial explains how to initialize a tokenizer, set filters, and fit it on text and vocabulary. It covers the creation of a word index to map words to numbers and discusses the concept of random tokenization. The tutorial concludes by introducing the next steps, which involve creating a train story, train question, and train answer.

What is the first step in setting up the tokenizer?

• Importing the tokenizer and setting filters

• Fitting the tokenizer on text

• Viewing the word index

• Preparing training data

Which command is used to fit the tokenizer on text?

• tokenizer.word_index

• tokenizer.fit_on_texts

• tokenizer.initialize

• tokenizer.randomize

What does the word index show?

• The randomization of sequences

• The filters applied to the tokenizer

• The numerical indices assigned to words

• The order of text processing

What is the purpose of random tokenization?

• To apply filters to the tokenizer

• To prepare the tokenizer for training

• To assign random indices to words

• To ensure words are processed in order

What are the next steps after random tokenization?

• Initializing the tokenizer

• Fitting the tokenizer on text

• Preparing training data for stories, questions, and answers

• Viewing the word index