Question: Which of the following steps are part of the model development process? Select all that apply.
- The model learns patterns in the training dataset and makes successful predictions over time
- Designers collect relevant data with which to train the model
- Discard the model
- The data is prepared for training
Explanation
Model development depends on relevant data because the system needs examples from which patterns can be identified. The data must be prepared so it is usable for training and does not introduce avoidable errors. During training, a machine learning model adjusts its behavior based on patterns found in the training data. This process supports prediction or output generation, but the final model still requires review before classroom use.
Why the other options are incorrect
Discard the model is incorrect because removing the model is not a standard step in building or training it.
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.