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What is a common challenge faced when applying neural networks in case studies?

Practice Questions

Q1
What is a common challenge faced when applying neural networks in case studies?
  1. Overfitting
  2. Underfitting
  3. Data scarcity
  4. High computational cost

Questions & Step-by-Step Solutions

What is a common challenge faced when applying neural networks in case studies?
  • Step 1: Understand what a neural network is. It is a type of computer program that learns from data.
  • Step 2: Learn about training data. This is the data we use to teach the neural network.
  • Step 3: Know what overfitting means. It happens when the neural network learns the training data too well.
  • Step 4: Realize the problem with overfitting. If the model is too focused on the training data, it won't perform well on new data.
  • Step 5: Understand that generalization is important. A good model should work well on both training data and new, unseen data.
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