I'm working on a school project where I need to build a credit score model for banking institutions. I'm considering using Amazon SageMaker for this purpose. Is that a good choice, or are there better options?
5 Answers
Honestly, using Excel might be the most straightforward approach for this project! It can handle the calculations you need easily without the complexities of more advanced tools.
Credit scores are generally calculated based on a set of rules rather than complex AI processes. You can create a formula based on various factors that affect the score, like payment history and age of accounts. SageMaker would be better suited for situations where you have a large dataset and want to predict scores for new instances.
Using SageMaker might lead to some pretty hefty bills, like around $2000! You might want to think about more cost-effective alternatives.
Did your instructor mention the need for AI or machine learning for this project? Credit score calculation is usually straightforward and might not require those complex methods.
You should definitely check in with your instructor first. They may not expect you to use something like SageMaker. Building the model in Python using libraries like pandas and sklearn could be much simpler, especially if you can create or find some training data. A Random Forest Classifier is often a solid choice for credit scoring tasks!

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