基于RFM和决策树模型构建专家推荐系统。融合了RFM模型和决策树模型，结合专业运营人员的业务经营，发掘潜在用户，进行推荐营销召回。

This project implements a real-time EEG (Electroencephalogram) signal processing and visualization system with epileptic seizure detection capabilities. The system combines machine learning for seizure detection with an interactive web interface for real-time signal monitoring and analysis.

Heart disease detection using different classifiers and neural network with feature engineering.

A Diabetes prediction Machine learning model using diagnostic data and algorithms such as logistic regression and decision trees. Evaluate their performance and deploy the top-performing model for accurate diabetes prediction.

ML application on wearable devices to predict a person's activities.

This repository covers a "Lending Club" analysis with decision tree and random forest with data visualizations and exploration.

This model is for detection of fake news using four different classifiers.

I tried to implemented two Data Mining theories in Object Detection Problem. One of them is Object Recognition with descriptive statistical feature, and the other one is with Decision Tree.

This repository contains a project for predicting house prices using multiple regression techniques and machine learning models, including boosting algorithms. The goal is to train several models on historical house price data and evaluate their performance using the R² score.

Predictive models for breast cancer classification using machine learning algorithms. Explore various classification techniques to identify malignant and benign tumors from medical imaging data.

This project aims to address the challenge of predicting whether it will rain or snow in Hungary based on various meteorological variables.

The repository contains sample Decesion tree ML models made on real world datasets

CROPIFY: An Intelligent System is a Smart Farming Assistant uses advanced technology, including machine learning and CNNs, to provide farmers with crop recommendations, disease identification, weather forecasts, and crop management guidance through a user-friendly web app.

To compare the performance of Large Language Models (LLMs) and Classical Machine Learning (CML) approaches in predicting COVID-19 mortality using a high-dimensional structured dataset.

The project focuses on identifying the speaker accent to be US or not US using binary classification. This project uses various Machine Learning classification methods like Logistic Regression, KNN, Binary Tree and Random Forests. Using the listed methods, evaluated the performance on the baseline models. To increase the accuracy and to prevent …

Data Science project for loan approval prediction

this project involves analyzing customer churn data to identify patterns and prevent customer churn by understanding the behaviors and characteristics that lead to it.