This repository contains analysis of churn in telephone service company (using IV and WOE), comparison of effect size and information value and quick tutorial how to use information value module (created for this analysis).

Find missing values in data set using Euclid distance, normalization and calculating information value, weight of evidence

Logistic Regression technique in machine learning both theory and code in Python. Includes topics from Assumptions, Multi Class Classifications, Regularization (l1 and l2), Weight of Evidence and Information Value

Weight of Evidence Encoding & Information Value

The objective of this project is to predict credit score of the borrowers using logistic regression and provide threshold cut-off recommendation

The objective of this project is to predict credit score of the borrowers using logistic regression and provide threshold cut-off recommendation

Implementation of weight of evidence and Information value techniques using Python

The repo consists of Statistics Algorithms

Credit Score Modelling: Perform a Weight of Evidence Logistic Regression Modelling (WoELR) to generate credit scorecard for loan approval with the help of optbinning library.

Capstone Project: Acquisition ScoreCard

Credit Score Modelling: Perform a Weight of Evidence Logistic Regression Modelling (WoELR) to generate credit scorecard for loan approval.

The creation of the credit risk prediction models of a lending company.

(Python) Proyecto enfocado en la creación de modelos predictivos como Regresión Logistica, Arboles de Decisión, KNN, SVM, Naive Bayes y Ensamblados. Inicialmente el problema consta de un analisis crediticio de clientes buenos/malos. Se utiliza una BBDD de clases desbalanceadas la cual se limpia y procesa para alimentar los modelos

This repo contains algorithms for data analysis required while building DL/ML models

Supporting materials for creating blog posts

Problem statment about modeling target vector and attempt to improve metrics

Machine Learning