The Loan Eligibility Prediction project will explain the workflow for assessing someone, whether or not a person is eligible for a loan using a machine learning model. The purpose of making this prediction is to help the lender determine whether a person is eligible or not given a loan.
- Pandas
- Numpy
- Seaborn
- Matplotlib
- scikit-learn
- Logistic Regression
- Decision Tree
- Random Forest
- Extra Tress
- Data Collection and Processing
- Exploratory Data Analysis
- Added New Feature to Dataset
- Doing Log Transformation to the Feature
- Label Encoding
- Training Model
- Hyperparameter Tuning
- Confusion Matrix Logistic Regression
In a Simple Term, Company wants to make automate the Loan Eligibility Process in a real time scenario related to customer's detail provided while applying application for home loan forms. That why, I try to create some project to solve that problem. When I used this Dataset, there are many new thing I have to learn until I can finish this project. I have attach Presentation file about this project. If you need to see my presentation for this project, you can visit my youtube channel. I also upload about this project in my LinkedIn, feel free to connect
https://bit.ly/LEP_rikasahriana
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