Question: An artificial intelligence design team performs the six steps of model development. What happens during the model-training step?
- Collect relevant data with which to train the model
- Prepare the data for training
- Iterate on the model over time
- The model learns patterns in the training dataset so it can make successful predictions over time
Explanation
During model training, the system uses prepared training data to identify patterns that support future predictions or outputs. The model adjusts its internal behavior as it processes examples from the training dataset. This step comes after data collection and preparation because the model needs usable data before learning can occur. Training is followed by evaluation and iteration to improve performance beyond the initial learning process.
Why the other options are incorrect
Collect relevant data is incorrect because that happens before training begins.
Prepare the data is incorrect because data preparation is a separate step completed before training.
Iterate on the model over time is incorrect because iteration happens after training and evaluation identify needed improvements.
Source for verification
https://cloud.google.com/learn/what-is-machine-learning
https://developers.google.com/machine-learning/crash-course/training-and-test-sets/splitting-data
The answer(s) to the question is highlighted in the BOLD text above. You can also find more questions and answers related to the exams on the "Generative AI for Educators" page.