Senior Data Engineer, Hogan Assessment Systems
Data Scientist, SwissRe
Data Engineer - Capacity Supply Chain and Provisioning, Microsoft India CoE
Data Scientist, Inmobi
In this loan prediction project you will build predictive models in Python using H2O.ai to predict if an applicant is able to repay the loan or not.
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Business Objective
When a customer applies for a loan at our company, we use statistical models to determine whether or not to grant the loan based on the likelihood of the loan being repaid. The factors involved in determining this likelihood are complex, and extensive statistical analysis and modelling are required to predict the outcome for each individual case.
Aim
You must implement a model that predicts if a loan should be granted to an individual based on the data provided
Tech Stack
Dataset Description
The dataset used is an anonymized synthetic data that was generated specifically for use in this project. The data is designed to exhibit similar characteristics to genuine loan data.
In this dataset, you must explore and cleanse a dataset consisting of over 1,00,000 loan records to determine the best way to predict whether a loan applicant should be granted a loan or not.
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