Home Loan Approval
Home Loan Approval Data Science Project
Classification in Depth with Scikit-Learn

Home Loan Approval

During this project, you will practice working with a real dataset, including loading, preparing, and cleaning the data, to train a machine learning model. The objective of this project is to assist lenders in making better-informed decisions when approving or denying loan applications.
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Project Activities

All our Data Science projects include bite-sized activities to test your knowledge and practice in an environment with constant feedback.

All our activities include solutions with explanations on how they work and why we chose them.

multiplechoice

Consider two models that each evaluate the same dataset.

Which one of the following statements is true?

multiplechoice

Which parameters below are hyperparameters of Logistic regression?

Choice the correct answer

multiplechoice

A model is overfitting when:

Choice the correct answer

multiplechoice

True or False: Machine learning involves training models to make accurate predictions on new, unseen data

multiplechoice

True or False:Evaluating a machine learning model solely on its accuracy is sufficient to determine whether it is a good model.

multiplechoice

What is the target variable?

multiplechoice

How many null values are present in the dataset?

multiplechoice

Are there any duplicate values in the dataset?

multiplechoice

Compute the number of people that is married.

input

Compute the correlation matrix.

Now calculate the correlation between all the variables: Which is the correlation between ApplicantIncome and LoanAmount?

Round to two decimals

multiplechoice

Which is the correct way to encode a variable?:

codevalidated

Submission

Now, let's submit your predictions for the test dataset to get a score from the platform.

Home Loan ApprovalHome Loan Approval
Author

Verónica Barraza

This project is part of

Classification in Depth with Scikit-Learn

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