What is a potential risk of deploying a machine learning model without proper validation?
Practice Questions
1 question
Q1
What is a potential risk of deploying a machine learning model without proper validation?
Increased training time
Overfitting
Poor user experience
Data leakage
Deploying a machine learning model without proper validation can lead to a poor user experience, as the model may not perform as expected in real-world scenarios.
Questions & Step-by-step Solutions
1 item
Q
Q: What is a potential risk of deploying a machine learning model without proper validation?
Solution: Deploying a machine learning model without proper validation can lead to a poor user experience, as the model may not perform as expected in real-world scenarios.
Steps: 5
Step 1: Understand what a machine learning model is. It is a program that learns from data to make predictions or decisions.
Step 2: Know that before using the model in real life, it needs to be tested. This is called validation.
Step 3: Realize that if the model is not validated, it might not work well when used by people.
Step 4: Consider that a poorly performing model can confuse users or give wrong information.
Step 5: Conclude that proper validation is important to ensure the model meets user needs and expectations.
