Machine Learning: Random Forest with Python from Scratch - Using Matplotlib for Data Visualization (2)

The video tutorial focuses on analyzing Titanic data to determine the number of singles and families who died. It begins with an introduction to the task, followed by extracting data for singles who perished. The instructor addresses errors in column names and reruns the code to ensure accuracy. The tutorial then calculates the number of people with families who died. It concludes with a summary of the task and introduces the next topic of data cleaning, including outlier removal and handling missing values.

What is the main objective of the task discussed in the video?

• To analyze the number of passengers who survived the Titanic.

• To display the number of singles and families who died on the Titanic.

• To find the number of crew members on the Titanic.

• To calculate the total number of passengers on the Titanic.

Which condition is used to filter singles who died on the Titanic?

• Survival equals 0 and sibling or spouse equals 0.

• Survival equals 1 and sibling or spouse equals 1.

• Survival equals 0 and parent or child equals 1.

• Survival equals 1 and parent or child equals 0.

What error was encountered during the filtering process?

• Syntax error in the code.

• Wrong column name used.

• Missing data in the dataset.

• Incorrect dataset used.

How is the number of people with families who died calculated?

• By dividing the total population by the number of singles.

• By multiplying the number of singles by two.

• By subtracting the number of singles from the total population.

• By adding the number of singles to the total population.

What is the total number of people with families who died on the Titanic?

• 374

• 1502

• 517

• 891

What type of plots were used for data visualization in this task?

• Bar plots

• Scatter plots

• Pie charts

• Line plots

What topic will be discussed in the next lecture?

• Data cleaning, including handling outliers and missing values

• Statistical analysis methods

• Advanced data visualization techniques

• Machine learning algorithms