TFM Comparativa de modelos de Machine Learning interpretables en riesgo crediticio
-
Updated
Nov 20, 2021 - Jupyter Notebook
TFM Comparativa de modelos de Machine Learning interpretables en riesgo crediticio
An analysis and prediction model for the Statlog (German Credit Data) dataset problem
Home Credit Default Risk project is to correctly offer loans to individuals who can pay back and turn away those who cannot
Credit risk analysis with R
The objective project is to decrease the company's losses by up to 30% through bad loans by creating a machine learning system to assist in automating loan assessments
Credit Risk Analysis using Python
As an intern Data Scientist at ID/X Partners, I'm involved involved in a project from a lending company to build a model that can predict credit risk using a dataset provided by the company which consists of data on loans accepted and rejected.
Data Analytics For Finance
Sample of Credit Risk model created with Scikit Learn allowing inference API with Flask.
This repository contains the Python scripts that I have written and run to execute a series of analytic model developments using datasets taken from the book "The Elements of Statistical Elements" by Hastie, Tibshirani, Friedman
Data Analysis project analyzing the characteristics of credit card borrowers. After the analysis, a classification model is built.
I built and evaluated several machine-learning models to predict credit risk using free data from LendingClub. I employed different techniques for training and evaluating models with imbalanced classes and used the imbalanced-learn and Scikit-learn libraries to build and evaluate models.
Source code for my Master Thesis in Credit Value Adjustment: Pricing Wrong Way Risk on Interest Rate Swaps
Credit risk prediction using Azure AutoML along with interpretable explanations.
A collection of machine learning mini-projects.
Credit Risk Analysis using Machine Learning models
Credit risk analysis: based on the number of family dependents and the duration of the month's loan, classify the credit rating or risk rating using the decision tree method (C50 with R).
financial risk management projects
This project is an endeavor to analyze the Risk of Default in Loan Repayment, with the prime objective being to provide invaluable insights that could be leveraged by banks for credit assessment of potential borrowers.
Add a description, image, and links to the credit-risk topic page so that developers can more easily learn about it.
To associate your repository with the credit-risk topic, visit your repo's landing page and select "manage topics."