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Determing the eligibility for granting home loan. ML classification models are used, in order to predict if loans are apporoved or not, based on customers's data.

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AntonioLunardi/Loan-Classification-Prediction-Competition-Case

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Project is still in progress...

Loan Classification Prediction Competition Case

The objective of the work is to automate the loan eligibility process (real time) based on customer detail provided while filling online application form.

🪧 Vitrine.Dev
✨ Nome Loan-Classification-Prediction-Competition-Case
🏷️ Tecnologias scikit-learn, numpy, matplotlib, pandas, Python
🔥 Desafio Problem statement link

About Dataset

Features present in the bank data frame are customers's gender, marital status, level of education, number of dependents, income, loan amount, credit history and others.

Content

This dateset was downloaded from AV website for practicing the eligibility of granting home loan. For further details please visit the website. https://datahack.analyticsvidhya.com/contest/practice-problem-loan-prediction-iii/#ProblemStatement.

Methodology

Build a binary classification model to predict the outcome:

  • Exploratory data analysis (EDA).
  • Feature engineering.
  • Data preprocessing.
  • Various models building and cross validation.
  • Performance metric selection.
  • Hiperparameters tuning.
  • Model selection.