Practice Good Data Characteristics (14.5.1) - Revisiting AI Project Cycle, Data
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Good Data Characteristics

Practice - Good Data Characteristics

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does it mean for data to be relevant?

💡 Hint: Think about how irrelevant data would affect a prediction.

Question 2 Easy

Why is accuracy important in data collection?

💡 Hint: Try to remember how mistakes can lead to wrong predictions.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What characteristic of data ensures it helps solve relevant problems?

Accuracy
Relevance
Completeness

💡 Hint: Consider what makes information applicable to your task.

Question 2

True or False: Clean data is essential for accurate predictions.

True
False

💡 Hint: Think about how dirty environments can affect clarity.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Imagine you are tasked with creating an AI model for predicting loan eligibility. Your dataset has significant gaps in data on applicants from different demographics. How would you address this issue while ensuring the model is fair?

💡 Hint: Consider strategies that can improve data collection processes.

Challenge 2 Hard

You find that your dataset contains many duplicates and errors, which seems to be affecting the model’s accuracy. List steps you would take to clean your data.

💡 Hint: Focus on organizing and structuring your cleaning process.

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