4.2. Principles of AI Application Design Methodologies

Try these first

1. 1.

   What is supervised learning?

   Hint

   Think about datasets that tell the model what the output should be.

2. 2.

   Why is data cleaning important?

   Hint

   Dirty data can lead to poor model performance.

3. 3.

   Which term refers to the limitation of learning too well from training data?

   • Overfitting
   • Underfitting
   • Regularization

   Hint

   Think about how well the model performs on unseen data.

4. 4.

   True or False: Unsupervised learning requires labeled data.

   • True
   • False

   Hint

   Recall what 'unsupervised' means.

5. 5.

   Design an AI application for predicting housing prices. Outline the steps you would take from problem definition to model evaluation.

   Hint

   Consider real estate data and the factors that influence housing prices.

6. 6.

   You need to develop a real-time image classification system for a drone. Discuss algorithm selection, data handling, and model training considerations.

   Hint

   Think about how drones operate and the need for quick decision-making.