Model Serialization
In MLOps, model serialization is the process of saving a trained machine learning model to a file. Implement a function to serialize a model using the NumPy library.
Example:
Suppose we have a trained linear regression model represented as a NumPy array. We want to serialize the model to a file for later use.
Constraints:
Test Cases
Test Case 1
Input:
[[1.0, 2.0], [3.0, 4.0]]Expected:
nullTest Case 2
Input:
[[5.0, 6.0], [7.0, 8.0]]Expected:
null+ 3 hidden test cases