Practice ML Fundamentals & Data Preparation - 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 machine learning?

πŸ’‘ Hint: Think about how the computer improves without human commands.

Question 2

Easy

Name two types of machine learning.

πŸ’‘ Hint: Consider the difference between labeled and unlabeled data.

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 is the primary goal of supervised learning?

  • To cluster data into groups
  • To predict outcomes from labeled data
  • To reduce dimensions

πŸ’‘ Hint: Think about what labeled data provides.

Question 2

True or False: PCA is used to increase the number of dimensions in data.

  • True
  • False

πŸ’‘ Hint: Consider what PCA aims to achieve.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You are given a dataset with missing values. Discuss the advantages and disadvantages of using deletion versus imputation to handle these values.

πŸ’‘ Hint: Consider data integrity and the potential impact on analysis.

Question 2

You have a dataset with high dimensionality. Explain how PCA can help improve your machine learning model's performance.

πŸ’‘ Hint: Think about model simplicity versus complexity.

Challenge and get performance evaluation