Practice Training Deep Neural Networks - 7.9 | 7. Deep Learning & Neural Networks | Advance Machine Learning
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7.9 - Training Deep Neural Networks

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is normalization in the context of training deep learning models?

💡 Hint: Think about why scaling might be needed in data processing.

Question 2

Easy

What does data augmentation help us achieve?

💡 Hint: Consider how it can help reduce model overfitting.

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 purpose of normalization?

  • To scale data to a standard range
  • To increase batch size
  • To reduce dataset size

💡 Hint: Remember how scaling impacts the training process.

Question 2

True or False: Data augmentation is performed on the validation dataset.

  • True
  • False

💡 Hint: Think about the purpose of validation datasets.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a deep learning training pipeline that includes dataset preparation, training phases, and hyperparameter tuning. Describe each step.

💡 Hint: Think about how each component influences the overall training success.

Question 2

Consider you have a dataset with imbalanced classes. Suggest a strategy for data augmentation to address this issue while training a neural network.

💡 Hint: Consider methods to increase the presence of underrepresented classes.

Challenge and get performance evaluation