Use auto encoder feature extraction to facilitate classification model prediction accuracy using gradient boosting models

A simple machine learning app to predict how much money a tourist will spend when visiting Tanzania.

Kaggle Gold Medal Solution. ICR - Identifying Age-Related Conditions.

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"

Supervised Machine Learning Model for Thyroid Disease Classification

Lab for testing multiple Machine Learning models using local traffic data to predict the average expected delay at a bus stop

Predicting H1N1 and seasonal flu vaccinations using survey data. Includes data preprocessing, exploratory data analysis (EDA), model experimentation, and evaluation of multilabel classification approaches.

This project focuses on predicting heart disease using a comprehensive dataset containing patient information. The goal is to build machine learning models that can predict the presence of heart disease based on various health parameters.

Binary classification preprocessing benchmark for auto-insurance data: binning/discretization + Random UnderSampling & SMOTETomek + feature transformations/engineering + PCA dimensionality reduction + evaluation with Logistic Regression & Histogram Gradient Boosting 🚗

Making a project for detecting bots and fraud in social media using Deep Learning & NLP.

ML model for prediction of diabetes based on dataset from a kaggle competition. Using HistGradientBoosting Algorithm

Airline Passenger Satisfaction prediction using sklearn

Encrypted VPN traffic classification using Random Forest, HistGradientBoosting and SHAP

This project studies lap time prediction in Formula 1 using ML models trained on telemetry, weather, and circuit data from the 2023–2025 seasons. Two complementary modeling settings are explored: Per-race models — trained and evaluated within a single race Per-circuit models — trained on multiple circuits and tested on unseen ones

🩺 Predict diabetes risk using an end-to-end machine learning pipeline, featuring advanced models and techniques for superior accuracy in the Kaggle competition.