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This is a induction motor faults detection project implemented with Tensorflow. We use Stacking Ensembles method (with Random Forest, Support Vector Machine, Deep Neural Network and Logistic Regression) and Machinery Fault Dataset dataset available on kaggle.
A user-friendly desktop application that utilizes a logistic regression model to predict the probability of a user having diabetes based on their inputted information.
Explore model selection in credit card transaction analysis with Reza Mousavi's Git project. Addressing class imbalance, it employs undersampling and features tree-based models, SVM, and logistic regression for effective fraud detection
This project presents a powerful Web Application Firewall (WAF) designed to protects web applications from malicious activities. By leveraging machine learning algorithms, the WAF efficiently filters and detects potentially harmful requests before they reach the website, ensuring robust security.
This repository contains code and analysis for detecting cancer using various machine learning algorithms. We compare the performance of logistic regression, decision tree, and random forest models.
This repository contains work that has been done on various concepts of Python like linear regression, logistic regression, decision tree, Random forest, KNN, and K-means algorithm
This project aims to detect fraudulent transactions in a dataset using machine learning models like Logistic Regression and Decision Tree. The dataset is highly imbalanced, and techniques like SMOTE are used to balance it.
This repository provides essential tools and metrics for evaluating binary classification models, aiding researchers and data scientists in their model assessment