Recommender Systems with Machine Learning - Data Manipulation for Content-Based Filtering

The video tutorial explains how to extract movie titles and years from a dataset using Python. It covers creating functions to separate titles from years, handling missing year data, and applying these functions to a dataset. The tutorial emphasizes the importance of understanding Python basics and provides a step-by-step guide to renaming columns and checking for missing values.

What is the main task described in the first section of the video?

• Extracting the director's name from a movie title

• Differentiating between the title and year in a movie title

• Finding the genre of a movie

• Calculating the length of a movie title

In the 'extract_title' function, what is the purpose of checking if the year is numeric?

• To determine if the year should be removed from the title

• To ensure the title is in uppercase

• To check if the title contains special characters

• To verify the title length

What does the 'extract_year' function return if no numeric year is found?

• The string 'unknown'

• The original title

• The integer 0

• NP dot NAN

What is the first step in applying the functions to the dataset?

• Filtering out movies without a year

• Sorting the dataset by year

• Renaming columns to include 'title_year'

• Deleting all existing columns

What is the purpose of the 'strip' function in the dataset processing?

• To sort the titles alphabetically

• To remove leading and trailing white spaces

• To convert all text to lowercase

• To add a prefix to each title

How many new columns are created after applying the functions to the dataset?

• Two

• Four

• One

• Three

What is the main focus of the fourth section?

• Creating a new dataset

• Applying functions to extract data

• Writing a new Python script

• Analyzing the extracted data

What is checked for in the year column after extracting titles and years?

• Incorrect formats

• Duplicate values

• Extra spaces

• Missing values

What is the next step mentioned after handling missing values in the year column?

• Calculating the average year

• Removing duplicate entries

• Sorting the dataset by title

• Exploring the genres available

What is the outcome of the process described in the video?

• A list of movie directors

• A dataset with separated titles and years

• A summary of movie genres

• A report on movie ratings