Practice Module Objectives - 1.1 | 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

Define supervised learning.

πŸ’‘ Hint: Think about how labels guide the learning process.

Question 2

Easy

What is imputation?

πŸ’‘ Hint: Recall how we handle gaps in 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 type of learning uses labeled data?

  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning

πŸ’‘ Hint: Focus on the concept of guidance in learning.

Question 2

True or False: Dimensionality reduction helps in reducing the number of features in ML.

  • True
  • False

πŸ’‘ Hint: Think about simplifying complex data.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Assess the impact of misapplying imputation techniques on a dataset likely to influence predictive accuracy.

πŸ’‘ Hint: Consider how imputation affects the underlying data distribution.

Question 2

Create a plan for a machine learning project from problem definition to model deployment, detailing each step.

πŸ’‘ Hint: Think through the workflow and what is necessary at each stage.

Challenge and get performance evaluation