A model classifying whether a person would survive on Titanic

Detección de cardiopatías en pacientes mediante el uso de datos clínicos utilizando técnicas de Machine Learning y Deep Learning.

classifying a patient has a heart disease or not

Amazon employee data to predict approval/ denial

This repository contains the project where the goal is to develop a machine learning model that can accurately predict car prices based on various features. We explored multiple models including K-Nearest Neighbor, Decision Tree, Catboost Classifier, and Light Gradient Boosting Classifier.

We all have experienced a time when we have to look up for a new house to buy. But then the journey begins with a lot of frauds, negotiating deals, researching the local areas and so on. So to deal with this kind of issues Today, I prepared a MACHINE LEARNING Based model, trained on the House Price Prediction Dataset.

Android malware detection using machine learning.

A ML model to predict whether the clients will subscribe to insurance or not.

This project utilizes advanced data analysis and machine learning techniques to predict equipment failures before they occur. The goal is to detect anomalies and possible defects in equipment and processes to enable preemptive maintenance, thereby reducing downtime and costs.

Address employee attrition effectively with this mini project. Discover a comprehensive solution leveraging data analytics and machine learning techniques. Uncover insights, build predictive models, and implement strategies to mitigate attrition risks, fostering a resilient and productive workforce.

Machine learning to predict which passengers survived the Titanic shipwreck

ML-solution of the case of the District hackathon Leaders of Digital 2023. The task was to predict accidents (accidents, pipe ruptures, fires) based on the weather forecast for each of the urban districts. Gradient boosting (macro f1), cross-validation, shap values.

A Domestic violence support system for the victims, that enables users to share their thought and provides knowledge about the particular type of abuse they are going through.

This project develops an advanced predictive model to identify thyroid disease recurrence using machine learning algorithms. We used a detailed dataset with demographic, medical, and clinical features, and implemented Logistic Regression, Decision Tree, Random Forest, and CatBoost Classifier. Rigorous preprocessing and EDA were performed.

A Breast Cancer Prediction Model

We all have experienced a time when we have to look up for a new house to buy. But then the journey begins with a lot of frauds, negotiating deals, researching the local areas and so on. So to deal with this kind of issues Today, I prepared a MACHINE LEARNING Based model, trained on the House Price Prediction Dataset.

Classification problem in Heart-Disease Data

Data Analysis and prediction on Kaggle dataset: Credit Risk Dataset

Educational project