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A machine learning project to predict loan defaults in a German bank's customer base. Using the German Credit Risk dataset, it explores key factors contributing to defaults and trains models like Random Forest, GBM, and XGBoost. Includes EDA, data processing, hyperparameter tuning, and model evaluation.

machine-learning random-forest exploratory-data-analysis xgboost accuracy gbm recall data-processing hyperparameter-tuning precision f1-score bagging ada-boost-classifier gridsearchcv missing-value-handling categorical-encoding modelevaluation randomsearch-cv

Updated Nov 24, 2024
Jupyter Notebook

luuisotorres / EDA-and-Employee-Attrition-Prediction

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Exploratory data analysis and machine learning classification models to predict employee attrition.

data-science machine-learning random-forest scikit-learn sklearn xgboost hyperparameter-optimization employee-management decision-tree-classifier gradient-boosting machine-learning-classification ada-boost-classifier employee-attrition sklearn-classifier xgboost-classifier randomsearch-cv

Updated Jul 14, 2022
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astonglen / Web-Mining-Project

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In this data analysis project, we embarked on a comprehensive exploration of Oracle's interview review data scraped from Glassdoor. Our objective was to gain valuable insights into the interview experiences of candidates applying for specific job postings at Oracle.

logistic-regression beautifulsoup random-forest-classifier selenium-python ada-boost-classifier webdriver-manager nltk-python

Updated Sep 10, 2023
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thirt33n / Grindwall

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ML Based Firewall System

machine-learning web monitoring random-forest network firewall ml waf web-security network-security ada-boost-classifier web-app-firewall ml-based-firewall

Updated Mar 11, 2024
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Abir0810 / Countries-Condition-Trees-percentage-and-forestation-using-Machine-Learing

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This is about machine learning model where there are many algorithms is using to find out best accuracy.

naive-bayes ann decision-tree gradient-boosting ada-boost-classifier svm-algorithm logistics-algorithm linear-discriminant-classifier

Updated Dec 15, 2020
Python

Kenner82 / Credit_Risk_Analysis

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Testing 6 different machine learning models to determine which is best at predicting credit risk.

python pandas ensemble-learning supervised-machine-learning ada-boost-classifier balanced-random-forest smote-oversampler naive-random-oversampler cluster-centroid-undersampling smoteenn-combination oversampling-algorithms undersampling-algorithms combination-sampling-algorithms

Updated Jan 23, 2023
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Jayveersinh-Raj / ML_algorithms_from_scratch

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This repository contains some Machine learning algorithms from scratch to better understand how they work, and are implemented under the hood.

linear-regression machine-learning-algorithms ada-boost-classifier knn-classifier

Updated Oct 26, 2022
Python

SaadTariq01DataAnalyst / Prediction-of-HouseGrade-Classification

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Prediction-of-House-Grade-Classification using python ( Jupyter Notebook)

data-science machine-learning-algorithms matplotlib classification-algorithm random-forest-classifier ada-boost-classifier stacking-classifier

Updated Aug 9, 2023
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Zauverer / Test-Crime-Analisys

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Boston Crime Analisys test.

python jupyter-notebook pandas seaborn logistic-regression gradient-boosting-classifier random-forest-classifier ada-boost-classifier joblib

Updated May 21, 2021
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dhruwsunita / Heart-Disease-Prediction

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Heart Disease Prediction Project using machine learning models.

data-science machine-learning numpy pandas logistic-regression decision-tree-classifier k-nearest-neighbours gradient-boosting random-forest-classifier ada-boost-classifier

Updated Jan 1, 2025
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virajbhutada / titanic-survival-prediction

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ML project focused on predicting Titanic passenger survival using various algorithms and extensive data analysis techniques. This project includes detailed data visualization and interpretation to uncover key factors affecting survival. By leveraging various ML models the analysis aims to achieve high predictive accuracy.

data-science machine-learning data-visualization logistic-regression data-exploration roc-curve hyperparameter-tuning decision-tree-classifier knn-classification model-interpretation random-forest-classifier ada-boost-classifier titanic-classification

Updated Jun 19, 2024
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GR8505 / Credit_Risk

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Performed supervised machine learning using oversampling, undersampling and combination sampling techniques to determine credit risk for bank customers.

random-forest scikit-learn smote ada-boost-classifier imblearn cluster-centroid-undersampling