Practice Dataset Preparation (7.9.1) - Deep Learning & Neural Networks
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Dataset Preparation

Practice - Dataset Preparation

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is normalization?

💡 Hint: Think about what happens to data scales when using machine learning.

Question 2 Easy

Name one technique for data augmentation.

💡 Hint: Consider how you might visually change an image.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the primary goal of normalization?

To increase dataset size
To speed up convergence during training
To simplify data
None of the above

💡 Hint: Think about why algorithms might struggle with inconsistent feature scales.

Question 2

True or False: Data augmentation can lead to overfitting.

True
False

💡 Hint: Consider the purpose of data augmentation in improving model performance.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

A dataset has features ranging from 0 to 100 and 1000 to 10,000. Explain how you would normalize these features for better training results.

💡 Hint: Focus on how feature scaling can affect learning.

Challenge 2 Hard

Design an experiment where data augmentation can improve image classification accuracy. Outline the methods you'll use and justify your choices.

💡 Hint: Reflect on the balance between diversity and relevance in training data.

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Reference links

Supplementary resources to enhance your learning experience.