AIF-C01 Question 37
Select 4An e-commerce company wants to develop a machine learning (ML) model to predict customer churn. The team is new to ML and wants to follow the ML development lifecycle. Which of the following steps should they take to ensure a successful implementation of their ML project?
- A
Define the business problem and determine the success criteria.
- B
Collect, clean, and prepare the dataset for model training.
- C
Deploy the model directly without testing to save time.
- D
Evaluate the model using appropriate metrics before deployment.
- E
Monitor the model's performance post-deployment and retrain if necessary.
Show answer and explanation
Correct answers: A, B, D, E
Explanation
The ML development lifecycle consists of several key stages, including defining the problem, preparing the data, training and evaluating the model, deploying it, and monitoring and maintaining it post-deployment. Each of these steps is essential to ensure the model performs well, aligns with business goals, and adapts to changing conditions. Skipping any of these steps, such as testing before deployment, can lead to suboptimal outcomes.
- A. Correct.
Defining the business problem and success criteria is the first step in the ML development lifecycle and ensures that the model is aligned with the business objectives.
- B. Correct.
Data collection, cleaning, and preparation are critical steps in the ML lifecycle as they directly impact the quality and performance of the model.
- C. Incorrect.
Deploying the model without testing goes against best practices in the ML lifecycle, as it may result in poor performance or incorrect predictions.
- D. Correct.
Evaluating the model with appropriate metrics ensures the model meets the success criteria and performs as expected before deployment.
- E. Correct.
Monitoring the model's performance post-deployment and retraining if necessary is part of the continuous improvement process in the ML lifecycle to address concept drift or data changes.