Which phase in the ML project lifecycle corresponds to the model learning from data?

Which phase in the ML project lifecycle corresponds to the model learning from data?

• A. Model training
• B. Data collection and preprocessing
• C. Model assessment
• D. Definition of problem or task

Answer: (A)

Learning from data happens during the training phase. In this stage the model’s parameters are updated based on the training data, using an objective like minimizing loss, which is how the model learns the patterns and relationships that map inputs to outputs. Data collection and preprocessing come before training to ensure clean, usable data and the right features, but they don’t involve parameter updates. Defining the problem or task sets goals and scope, but no learning occurs yet. Model assessment happens after training, evaluating performance on new data rather than the learning process itself. So, the phase where the model learns from data is training.

Learning from data happens during the training phase. In this stage the model’s parameters are updated based on the training data, using an objective like minimizing loss, which is how the model learns the patterns and relationships that map inputs to outputs. Data collection and preprocessing come before training to ensure clean, usable data and the right features, but they don’t involve parameter updates. Defining the problem or task sets goals and scope, but no learning occurs yet. Model assessment happens after training, evaluating performance on new data rather than the learning process itself. So, the phase where the model learns from data is training.