Real Time Face Recognition with Python and OpenCV2, Create Your Own Dataset and Recognize that. #FreeBirdsCrew

Classification problem using multiple ML Algorithms

For this project, I used four different classification algorithms to detect fraudulent credit card transactions.

A machine learning project to predict loan defaults in a German bank's customer base. Using the German Credit Risk dataset, it explores key factors contributing to defaults and trains models like Random Forest, GBM, and XGBoost. Includes EDA, data processing, hyperparameter tuning, and model evaluation.

This is about machine learning model where there are many algorithms is using to find out best accuracy.

In this data analysis project, we embarked on a comprehensive exploration of Oracle's interview review data scraped from Glassdoor. Our objective was to gain valuable insights into the interview experiences of candidates applying for specific job postings at Oracle.

ML Based Firewall System

Testing 6 different machine learning models to determine which is best at predicting credit risk.

This repository contains some Machine learning algorithms from scratch to better understand how they work, and are implemented under the hood.

Prediction-of-House-Grade-Classification using python ( Jupyter Notebook)

Various Machine learning algorithms

Supervised Machine Learning and Credit Risk

Boston Crime Analisys test.

ML project focused on predicting Titanic passenger survival using various algorithms and extensive data analysis techniques. This project includes detailed data visualization and interpretation to uncover key factors affecting survival. By leveraging various ML models the analysis aims to achieve high predictive accuracy.

Classifying customers into segments

Heart Disease Prediction Project using machine learning models.

Predicting toxicity of molecules. Project on course "Data Mining 2"

Performed supervised machine learning using oversampling, undersampling and combination sampling techniques to determine credit risk for bank customers.