ml-engineer-pro video for you are employed at a bank, and you've developed a customized model to determine whether a loan application should be flagged for
You are employed at a bank, and you've developed a customized model to determine whether a loan application should be flagged for human review. The input features required for this model are stored within a BigQuery table. The model has exhibited strong performance, and you are in the process of preparing it for deployment in a production setting. However, due to compliance requirements, it is now imperative that the model provides explanations for each prediction it makes. Your objective is to incorporate this explanatory capability into your model's code with minimal effort while ensuring that the explanations offered are as accurate as possible. How should you proceed to accomplish this?