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.

Machine Learning, EDA, Binary Classification task weather dataset, ANN, SVM, LR

Machine Learning, EDA, Classification tasks, Regression tasks for customer churn

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.

Machine Learning Classification For Disease Prediction

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.

We took an iris dataset and trained with different classifiers to find out their accuracy and some parameters.

This project is dedicated to implementing various machine learning algorithms from scratch to gain a deeper understanding of how they work.

Machine Learning Tutorial

AI Machine learning Deep learning Projects with code

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

Projects for the Intelligent Systems course

This repository provides essential tools and metrics for evaluating binary classification models, aiding researchers and data scientists in their model assessment

📱 Customers are likely to leave a telecom service, enabling companies to take measures for retention and create accurate churn prediction models.

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.

🎓 Collection of academic resources, projects, and exercises related to artificial intelligence concepts learned in university coursework.

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

ACRE is an end-to-end application that leverages machine learning to predict customer churn and automates the retention process. This tool provides an interactive interface to identify high-risk customers and triggers an intelligent workflow to proactively engage them with retention offers.

IBM Data Science Capstone Project from Coursera

A ML project to predict sales for Black Friday.

Interactive credit card fraud detection simulator with real-world data, ML scoring, and visualization.

Chronic Kidney Disease Prediction Using ML | Website |

Batch Name: MIP-ML-11 (Machine Learning Intern)

Predicting whether a user clicks on an online advertisement using Logistic Regression and user behavior data.

No description provided.

A project to classify the Edibility of mushroom-based on its physical features.

Comparison of classification models over digits dataset

Performed different types of machine learning algorithms like linear regression, logistic regression, Decision Tree, Random forest.

A Machine Learning project in which we load, train and test our dataset. We also create a JSon File to run, deploy and test our model in cloud environment.