Practice Lab Objectives - 1.5.1 | Module 1: ML Fundamentals & Data Preparation | Machine Learning
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the purpose of using Jupyter Notebook in machine learning?

πŸ’‘ Hint: Think about its interactivity and ease of code execution.

Question 2

Easy

How do you load a dataset into a Pandas DataFrame?

πŸ’‘ Hint: Recall the function specifically designed for importing CSV files.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

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?

  • NumPy
  • Pandas
  • Matplotlib

πŸ’‘ Hint: Think about the library primarily associated with data manipulation.

Question 2

True or False: Visualizations in EDA are only relevant for categorical data.

  • True
  • False

πŸ’‘ Hint: Consider the types of data you would visualize.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You are given a dataset that contains information about students’ exam results with several missing values. Describe how you would handle the loading, inspecting, and visualizing of this dataset.

πŸ’‘ 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.

πŸ’‘ Hint: Consider not only the data itself but also what surrounding factors might clarify the outlier.

Challenge and get performance evaluation