Recommender Systems with Machine Learning - Rating Plot

The video tutorial covers the analysis of a movies dataset and a ratings dataset. It begins with checking the shape of both datasets, followed by exploring the columns in the ratings dataset. The tutorial then focuses on plotting the rating distribution using a horizontal bar plot, providing insights into how many users gave specific ratings. Finally, it examines unique user and movie IDs within the ratings dataset, offering a comprehensive understanding of the data structure and distribution.

What is the first step in analyzing the movies and ratings datasets?

• Checking the unique user IDs

• Filtering the data

• Checking the shape of the datasets

• Plotting the rating distribution

How many columns does the ratings dataset have?

• Four

• Five

• Three

• Two

Which columns are present in the ratings dataset?

• User ID, Movie ID, Genre

• User ID, Genre, Rating

• Movie ID, Rating, Genre

• User ID, Movie ID, Rating

What type of plot is used to display the rating distribution?

• Scatter plot

• Line plot

• Horizontal bar plot

• Pie chart

What is the purpose of setting the font size in the plot?

• To change the color of the plot

• To adjust the size of the plot

• To sort the data

• To enhance the readability of labels

What does the X label represent in the rating distribution plot?

• User ID

• Rating

• Movie ID

• Count

What is the next step after analyzing the rating distribution plot?

• Checking the shape of the datasets

• Identifying unique users and movie IDs

• Filtering the data

• Plotting a pie chart