Advanced Chatbots with Deep Learning and Python - Data Preparation

The video tutorial explains how to handle train and test data files in a program. It covers loading data from pickle files, checking data types and lengths, and exploring the structure of the data, which includes stories, questions, and answers. The tutorial concludes with a preparation for joining data to extract vocabulary and develop a set of stories and questions for training a chatbot.

What are the two types of question-answer files mentioned in the video?

• train_QA and test_QA

• input_QA and output_QA

• data_QA and result_QA

• question_QA and answer_QA

Which file format is used to store the question-answer data?

• CSV

• XML

• Pickle

• JSON

What is the data type of the loaded test data?

• Dictionary

• Set

• List

• Tuple

How many entries are there in the test data list?

• 1500

• 1000

• 2000

• 500

What is the format of the data entries in the train data?

• A question and an answer

• A list of numbers

• A story, a question, and an answer

• A single sentence

What is the question asked in the example story provided?

• Is Sandra in the hallway?

• Is Mary in the kitchen?

• Did Sandra move to the bedroom?

• Is Mary in the bathroom?

What is the next step after showcasing the data format?

• Convert the data to a different format

• Save the data to a new file

• Join the data for vocabulary extraction

• Delete the data