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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the purpose of using Jupyter Notebook in machine learning?
π‘ Hint: Think about its interactivity and ease of code execution.
Question 2
Easy
How do you load a dataset into a Pandas DataFrame?
π‘ Hint: Recall the function specifically designed for importing CSV files.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What library is primarily used to create DataFrames in Python?
π‘ Hint: Think about the library primarily associated with data manipulation.
Question 2
True or False: Visualizations in EDA are only relevant for categorical data.
π‘ Hint: Consider the types of data you would visualize.
Solve 1 more question and get performance evaluation
Push your limits with challenges.
Question 1
You are given a dataset that contains information about studentsβ exam results with several missing values. Describe how you would handle the loading, inspecting, and visualizing of this dataset.
π‘ Hint: Think about the steps logically: loading, identifying issues, and exploring.
Question 2
Imagine you have visualized a dataset and found an outlier in exam scores. Describe how you would want to analyze this outlier further.
π‘ Hint: Consider not only the data itself but also what surrounding factors might clarify the outlier.
Challenge and get performance evaluation