My Master Degree Project

Prediction of hospital length of stay at time of admission using support vector classifier

Credit Card Fraud Detection algorithm using smote , confusion matrix, correlation matrix, density plots and ROC-AUC curve . Model - Logistic Regression, Knn, Isolation Forest

Classification Model (End to End Classification of Heart Disease - UCI Data Set)

Clustering validation with ROC Curves

This project aims to create a classifier that can predict whether or not a candidate will change their job by using historical data on candidate demographics and details about their education and experience using different classification machine learning models.

Data Science : Youtube Vídeo Recommender on Python with youtube-dl. Predictive models with: DecisionTreeClassifier, RandomForestClassifier, TfidfVectorizer.

Maximizing Bank's Profitability

Naive Bayes, Confusion Matrix, and ROC Analysis were conducted using R to determine how different variables lead to a customer of a bank taking out a personal bank loan.

Built a logistic regression model and a classification tree model for predicting the final status of a loan based on various variables available. Confusion matrix and misclassification rate for each model for a test dataset. Variables that appear to be important for predicting outcome. Plotted and described the ROC curves and AUC for the four mo…

Projet de modélisation supervisée - SCORING

Wolfram Language (aka Mathematica) paclet for Receiver Operation Characteristic (ROC) functions.

Predict and prevent customer churn in the telecom industry with our advanced analytics and Machine Learning project. Uncover key factors driving churn and gain valuable insights into customer behavior with interactive Power BI visualizations. Empower your decision-making process with data-driven strategies and improve customer retention.

To predict which customer is most likely to convert

This project demonstrates how to build a logistic regression model and understanding the evaluation metrics to determine if the model is performing well or not

This Prediction is a research analysis process on data using classification algorithms to compare the accuracy rate for each algorithm given below on this Monkey Pox data such as ( K-Neighbors Classifier, RandomForest Classifier, AdaBoost Classifier, Bagging Classifier, Gradient Boosting Classifier, Decision Tree Classifier )

💉 Vaccine Sentiment Classifier is a deep learning classifier trained on real world twitter data, that distinguishes 3 types of tweets: Neutral, Anti-vax & Pro-vax.

The primary objective s to develop an accurate and efficient classification model capable of identifying pneumonia cases in patients based on chest X-ray images. Pneumonia is a prevalent and potentially life-threatening respiratory infection. Early detection plays a critical role in timely intervention and effective treatment.

ROC visualization tool for multi-class data