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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.
Advancing Cybersecurity with AI: This project fortifies phishing defense using cutting-edge models, trained on a diverse dataset of 737,000 URLs. It was the final project for the AI for Cybersecurity course in my Master's at uOttawa in 2023.
This repository provides a complete pipeline for non-invasive blood glucose estimation using Photoplethysmography (PPG) signals. It includes data preprocessing, feature extraction, machine learning model training, and result visualization to support research and development in biomedical signal analysis and diabetes screening.
Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or denied.
This repository contain my final projekt on the Data science Skillbox school on the topic: "Development of a machine learning algorithm to predict the behavior of customers of the "SberAvtopodpiska"
Analyzed time-series data (Depressjon) to detect depression from patient activity recorded via clinical actigraphy watches. Utilized features such as time domain, statistical metrics, and LSTM-extracted attributes.
This project aims to predict the selling prices of used cars based on various features such as brand, model year, mileage, and engine specifications.using-Stacking-ensemble-modeling-technique
This project presents a ML based solution using Ensemble methods to predict which visa applications will be approved and thus recommend a suitable profile for applicants whose visa have a high chance of approval