Advanced Chatbots with Deep Learning and Python - Tokenizer

The video tutorial explains how to initialize and fit a tokenizer 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 with a brief introduction to the next steps, which involve training a story, question, and answer.

What is the first step in setting up the tokenizer?

• Creating a train story

• Importing the tokenizer and setting filters

• Fitting the tokenizer on text

• Generating the word index

Which command is used to fit the tokenizer on vocabulary?

• tokenizer.word_index

• tokenizer.initialize

• tokenizer.fit_on_texts

• tokenizer.set_filters

What does the word index show?

• The frequency of each word

• The synonyms of each word

• The length of each word

• The number assigned to each word

How many vocabulary sequences are mentioned in the video?

• 40

• 37

• 38

• 39

What is the next step after generating the word index?

• Re-fitting the tokenizer on new text

• Creating a train story, question, and answer

• Adding more filters

• Re-initializing the tokenizer