SeoBuAs/Factor_Analysis-Predicting_Musical_Residual_Seats

Factor Analysis with a Framework for Predicting Musical Residual Seats Using Machine Learning / My Paper 1

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maheshvarade/Poland-Bankruptcy-Prediction

Poland Bankruptcy Prediction (2009) This project aims to predict whether a Polish company went bankrupt in 2009 based on its financial data. The dataset contains several features derived from companies' balance sheets, and the goal is to build models that can identify bankruptcy effectively — despite the challenge of high class imbalance.

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MathUPTC/Credit-Card-Fraud-Detection

Clasificación de transacciones de tarjetas de crédito con el fin de detectar anomilas

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sanjurajveer/Fraud_detection

Model for categorising transactions into fraud or not

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razamehar/Predicting-Bank-Customer-Churn

This project aims to predict bank customer churn using a dataset derived from the Bank Customer Churn Prediction dataset available on Kaggle. The dataset for this competition has been generated from a deep learning model trained on the original dataset, with feature distributions being similar but not identical to the original data.

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anirudh-pulavarthy/Car-Evaluation-using-SMOTE

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srusam/Applied-Data-Science-

This repository contains hands-on Jupyter notebooks for Applied Data Science concepts, experiments, and projects. The notebooks cover data cleaning, visualization, feature engineering, machine learning, and more, using Google Colab for execution.

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maheshvarade/Tree-Based-Algorithms-on-loan-data

Loan Risk Prediction Implemented RandomForestClassifier, which provided the best results compared to Gradient Boosting.Car Ownership Prediction (Using Same Data) Compared multiple models.House Ownership Prediction Followed the same pipeline for predicting House Ownership.

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rohitdwivedula/enzyme-classification

Predict the enzyme class of a given FASTA sequence using deep learning methods including CNNs, LSTM, BiLSTM, GRU, and attention models along with a host of other ML methods.

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RampageousRJ/Spam-Email-Detection

Detects if an outgoing mail would be classified as spam or not

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ThiagoMonica/nba-roy-prediction

🏀 Machine learning-based analysis to predict the NBA Rookie of the Year, identifying key player attributes using statistical modeling and classification algorithms.

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anushkundu/Churn-Prediction

Telecom Customer Churn Prediction Using Machine Learning!

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bsap16/risco_relativo

Um banco solicitou que fosse automatizado o processo de aprovação de empréstimos dos clientes.

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udit-rawat/Gan-n

A experimental project that delves in dealing with CI dataset using SMOTENN+GAN with dvc experimentation.

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Radhikareddy-chintareddy/Predictive-Churn-Modeling-Machine-Learning-for-Customer-Retention

This project employs machine learning algorithms to predict customer churn by analyzing historical customer data. It provides actionable insights to enhance customer retention. The models were fine-tuned using hyperparameter optimization and tackled data imbalance with SMOTE, achieving high F1-scores to drive targeted business strategies.

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lazybug19/FakeAlert

A fake news detection app leveraging Ensemble ML models and NLP context-analysis to evaluate the credibility of news articles by cross-referencing claims with reliable databases.

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TienNguyen93/diabetes-prediction

Implement a suite of ML algorithms to improve diabetes prediction

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ericmckevitt/Premier-League-Goal-Prediction

In this project, I am predicting goals scored by Premier League players using a Random Forest Regressor.

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aniass/Spam-detection

Spam detection in SMS messages with BERT model and Machine Learning algorithms

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Sama-Amr/Loan-Approval-Machine-Learning-Project

A machine learning project using python aiming to benefit the banking industry and reduce the hassle, pressure and workload and increase the efficiency and effectiveness of the process of issuing loans

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SundareshSankaran/SDG---SMOTE-Synthetic-Data-Generation

Upstream repository for a custom step to generate synthetic data based on an input table, using the Synthetic Minority Oversampling TEchnique (SMOTE). SMOTE is an oversampling technique which identifies new data observations in the neighborhood of closely associated original observations.

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venumadhav2407/MicroSoft-Classifying-Cybersecurity-Incidents

MicroSoft CyberSecurity Incident Classification

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Parag000/Customer-Churn-Prediction

An end to end ML solution to predict customer churn, aiding businesses in identifying at-risk customers. This repository features a tuned LightGBM model, custom preprocessing, SMOTE for class balancing, and a user-friendly Streamlit app for predictions, emphasizing model optimization and deployment.

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dpgitaccount/Project---Hospital-Readmission-Analysis

The goal of this project is to build a predictive model to estimate the likelihood of a hospital readmission based on patient data. By identifying factors that contribute to readmissions, hospitals can optimize care and reduce costs associated with repeated visits.

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Sharvari289/Deep-Learning-models-for-Imbalanced-Time-Series-Clinical-dataset

Deep Learning models aimed at improving performance on imbalanced time-series clinical data. The project explores data augmentation techniques and model optimization to enhance classification results in challenging imbalanced datasets.

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tathithienthanh/DataAnalysis_Diagnosis-of-diabetes-based-on-data-set-of-blood-test-result

Implement all learned knowledge about data analysis and data mining to make a complete project about Diagnosis of diabetes based on data set of blood test result

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apurvanand-2002/Dealing-with-imbalanced-data

Using Random undersampling, Tomeklinks, Random oversampling, SMOTE, SMOTE+Tomeklinks and ADASYN from inbuilt imbalanced learn library and found how many records added or discarded.

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apurvanand-2002/SMOTE-

SMOTE code ( used from imblearn) along with classification report and confusion matrix usage. Also, created our own dataset using make_classifcation() function of python.

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SeyedMuhammadHosseinMousavi/SDGbySMOTE

Synthetic Minority Over-sampling Technique (SMOTE) for Synthetic Data Generation (SDG)

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manjugovindarajan/RENEWIND-predictive-maintenance-cost-maintenance-usingML

The aim is to decrease maintenance cost of generators used in wind energy production machinery. This is achieved by building various classification models, accounting for class imbalance, tuning on a user defined cost metric (function of true positives, false positives and false negatives predicted) & productionizing model using pipelines

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varmatilak22/Spam_SMS_Classification

This project aims to develop a machine learning model to classify SMS messages as spam or not spam. The project encompasses the entire pipeline from data collection and preprocessing to model training, evaluation, and deployment using Streamlit for an interactive user interface.

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dixon2004/credit-card-fraud-detection

This project employs machine learning and SMOTE to accurately identify fraudulent credit card transactions and address data imbalance.

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itsatefe/Machine-Learning

Machine Learning Algorithms

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andresaftari/MoniFlora-ModelTraining

Model Training for MoniFlora Mobile, connected to http://andresaftari.pythonanywhere.com/

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Niteshchawla/OLA-EnsembleLearning

Recruiting and retaining drivers is seen by industry watchers as a tough battle for Ola. Churn among drivers is high and it’s very easy for drivers to stop working for the service on the fly or jump to Uber depending on the rates.

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Niteshchawla/LoanTap-LogisticRegression

Given a set of attributes for an Individual, determine if a credit line should be extended to them. If so, what should the repayment terms be in business recommendations?

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Ezgigunbatar/ToxicityDetection

Toxicity detection on imbalanced social media data. Focused on 2 main topics of toxicity detection: Class imbalance problem and detecting toxic comments.

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dimitrisbro/SmartGridFraudDetection

Electricity Fraud Detection in Smart Grids

Language: Python - Size: 121 MB - Last synced at: 6 months ago - Pushed at: over 4 years ago - Stars: 9 - Forks: 5

Gustaminas/AI_primer---Bank_Marketing

A project from the AI_primer course at Vilnius university.

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IgnOrtega/Financial-payment-system-Fraud

Este proyecto consiste en la detección de fraudes utilizando machine learning, datos desbalanceados y técnicas de muestreo.

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abis330/footbalysis

Player Rating System in Soccer using Machine Learning

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UdbhavSrivastava/Stroke-Predictive-Modeling

This study uses predictive analytics to detect stroke risk factors early, aiming to reduce occurrences. By analyzing risk factors with machine learning, it uncovers patterns and correlations. Models such as Logistic Regression, KNN, Decision Trees, Random Forest, and Neural Network.

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fitria-dwi/Credit-Risk-Prediction

This project aims to identify patterns that indicate if a person is unlikely to repay the loan or labeled as bad risk and build a predictive model to predict loan risk from applicants.

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tomartushar/Credit-Card-Fraud-Detection

An ensemble of machine learning models for detecting fraudulent credit card transactions, utilizing advanced techniques for feature selection, data imbalance handling, and hyperparameter tuning.

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princessEmilyy/ML-project-diabetes-

Project for applied classical ML course at the Weizmann institute

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dardenkyle/Credit-Card-Users-Churn-Prediction

Analyze the data and come up with a predictive model to determine if a customer will leave the credit card services or not and the reason behind it

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ShyrenMore/sem08

A compilation of codes for SMA, DC, ADS

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vrbabu9000/bank_termDeposit_predictor

Given a highly biased banking dataset of 45k entries and 17 variables wherein I was able to filter out good predictors for modelling and further balance the bias in the dataset using SMOTETomek method. The bias removal was approached in two different ways and the pros and cons of both methods are stated. The end result is a logistic regression model with 81% accuracy and striking a sharp balance between precision and recall with the former having a slight upper hand.

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Srijha09/Detection-Of-Fraudulent-Claims-In-Medical-Insurance

Checking whether the claims are fraud or non-fraud based on various attributes using Medicare Dataset

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Safaa-p/Fraudulent-Insurance-Claims-Detection

Different models to detect if a claim is fraudulent or not

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haniye6776/outlier-detection

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Akshadachavan02/classification-_algo

As the there are couple of classification algorithms in supervised machine learning so some of them as here..

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dsvirenpai/KNN_Forensic_Science_Classifying_GlassType

KNN in Forensic Science: Classifying Glass Evidence for Criminal Investigations

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ajitsingh98/E-commerce-product-buyer-session-prediction

Predict whether customer purchase a product or not in a session

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Theofilusarifin/Diabetes-Disease-Prediction

Diabetes, characterized by high blood sugar levels due to ineffective insulin production or usage, poses serious health risks if not managed. Deep Learning offers promising avenues for diabetes management.

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sumitkutty/Respondent-Group-Classification

6-class classification problem on a large dataset using machine learning.

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ggjay9/Application-Flow-Identification

Classify applications using flow features with Random Forest and K-Nearest Neighbor classifiers. Explore augmentation techniques like oversampling, SMOTE, BorderlineSMOTE, and ADASYN for better handling of underrepresented classes. Measure classifier effectiveness for different sampling techniques using accuracy, precision, recall, and F1-score.

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nickjlupu/Credit-Risk

Supervised scikit-learn machine learning models using several sampling techniques.

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garick161/alpha_bank_cup_challenge_final

Разработка алгоритма привлечения новых клиентов банка

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ceenaa/fraud_detection

Credit Card fraud detection

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epicure24/Classifier-for-highly-unbalanced-data

This repo represents all the resampling techniques needed to achieve better results in highly unbalanced or skewed data that has 77 % of data in one class and rest in others.

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MsTao-68/Debt-Churn-Data-Analysis

使用比赛方提供的脱敏数据，进行客户信贷流失预测。

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aryamaansaha/employeeattrition

This repository contains code that was used to predict employee attrition using machine learning methods.

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letstryy/LeadScoring

Predictive Lead Scoring using clickstream data

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ishreya09/Parkinson-Prediction-Model

We train different models and apply techniques gives us better evaluation metrics, and find out the best model which works the best for Parkinson's Prediction System

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shivamverma26/Credit_Card_Fraud_Detection

This project is dedicated to advanced machine learning techniques for credit card fraud detection, providing a solution to protect financial institutions and their clients by predicting and preventing fraudulent transactions in a highly imbalanced dataset.

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Er-Devanshu/Road-Severity-Classification

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skinan/Improved-Sampling-and-Feature-Selection-to-Support-Extreme-Gradient-Boosting-For-PCOS-Diagnosis

This project is a part of the research on PolyCystic Ovary Syndrome Diagnosis using patient history datasets through statistical feature selection and multiple machine learning strategies. The aim of this project was to identify the best possible features that strongly classifies PCOS in patients of different age and conditions.

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Angienoelhaverly/Credit_Risk_Analysis

Perform a Credit Risk Supervised Machin Learning Analysis using scikit-learn and imbalanced-learn libraries.

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SarangGami/Bank-Marketing-Effectiveness-Prediction-supervised-learning

The main objective is to build a predictive model that predicts whether a new client will subscribe to a term deposit or not, based on data from previous marketing campaigns.

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abhijha3011/Techniques-To-Handle-Imbalanced-Data

Different Techniques to Handle Imbalanced Data Set

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yrnigam/UCI_Credit_Card_Default

This dataset contains information on default payments, demographic factors, credit data, history of payment, and bill statements of credit card clients in Taiwan from April 2005 to September 2005.

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HRX101/Employee-satisfaction

Explainable AI for Predictive Analytics on Employee Satisfaction

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j1bulbul/Term_Deposit_Subscription_Predictor_ML

Supervised Learning, Binary Classification ML problem utilised to determine if an individual would subscribe to a term deposit based on various marketing characteristics

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joanitolopo/eval-sampling-methods

🔍 Evaluating Sampling Techniques for Healthcare Insurance Fraud Detection in Imbalanced Dataset.

Language: Python - Size: 188 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

sharmasapna/credit-card-fraud-detection

Code to detect credit card fraud detecton

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theheisenberg10/Facebook-Post-Sentiment-Analysis-NLP-using-RNNs

Predicting sentiment of Facebook posts (Appreciation, Complaint, or Feedback) using RNNs

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AI-14/lumpy-skin-disease-classification

Binary classification of lumpy skin disease (imbalanced dataset) using ML algorithms in addition to oversampling/undersampling techniques.

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Niranjan-stat/Loan-Default-Prediction

This project aims to provide a robust and accurate solution to the loan defaulting problem, helping financial institutions make more informed lending decisions and reduce their risk exposure.

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nazgol-nikravesh/NSGRT

Source code for "Cross-project Defect Prediction with An Enhanced Transfer Boosting Algorithm"

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krishna-aditi/credit-card-fraud-detection-imbalanced-dataset-problem

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technisekai/sentiment-analysis-of-new-halal-logo

:round_pushpin: Final project of Telkom Institute of Technology Purwokerto

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M-Hashemzadeh/RCSMOTE

RCSMOTE: Range-Controlled Synthetic Minority Over-sampling Technique for handling the class imbalance problem

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rikhuijzer/Resample.jl

An implementation of SMOTE

Language: Julia - Size: 3.73 MB - Last synced at: 4 days ago - Pushed at: over 1 year ago - Stars: 8 - Forks: 0

FataiAzeez/stroke_prediction_rf_svm_lr

This repo evaluates Logistic Regression, Random Forest, and Support Vector Machine models for predicting stroke risk. Implemented in Python, the project includes data pre-processing, model training, and performance metric calculations

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Palemravichandra/customer-segmentation

customer segmentation of insurance comapany

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Candida18/ADS_SMA

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yourssincerely/eurovision

This project provides a comprehensive analysis of the Eurovision Song Contest, with insights derived from both traditional statistical methods and machine learning techniques.

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avr2002/credit-card-default-prediction

This a classic Credit Card Default Prediction project where based on customer profile we want to predict whether the borrower is likely to default in the next 2 years or not having a delinquency of more than 3 months.

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urmipandya123/Road_Severity_Classification

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MoinDalvs/Assignment_SVM_Forest_Fire_Prediction

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AvinandanBose/Credit-Card-Fraud-Detection-Machine-Learning-

Credit Card Fraud Detection using Python and Machine Learning.

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bharatkulmani/Dry-Bean

Project is about predicting Class Of Beans using Supervised Learning Models

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sahidul-shaikh/credit-card-fraud-detection

Machine learning model for Credit Card fraud detection

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rochitasundar/Predictive-maintenance-cost-minimization-using-ML-ReneWind

The aim to decrease the maintenance cost of generators used in wind energy production machinery. This is achieved by building various classification models, accounting for class imbalance, and tuning on a user defined cost metric (function of true positives, false positives and false negatives predicted) & productionising the model using pipelines.

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rupeshsure/Obstructive-Sleep-Apnea-Project

Obstructive Sleep Apnea classification with help of numerical data set which having the physical body characteristics with the help of machine learing

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LeHongNgoc3820/Project_Credit_Card_Fraud_Detection

Credit Card Fraud Detection using Machine Learning Algorithms

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ankit-kothari/Credit-Risk-Analysis

Predicting the ability of a borrower to pay back the loan through Traditional Machine Learning Models and comparing to Ensembling Methods

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chebroluharika/credit-card-fraud-detection

Machine learning model for Credit Card fraud detection

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LokeshSreenathJ/Bankruptcy-Prediction---Analytics

Built XGBoost Classifier using SMOTE technique and Hyper-Parameter Tuning

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