A machine learning project to predict diabetes using a Support Vector Classifier model. It includes data preprocessing, model training, evaluation, and a Flask web application for real-time predictions.

Classifying Criminal Offenses: Classification Application in Python Using scikit-learn and TensorFlow-Keras

Exploratory data analyzing of Global Financial Database and loan borrowing prediction using PySpark

Implementation of non-linear models for regression analysis of concrete strength and classification of wine.

Loan Eligibility Prediction Model: A machine learning application to predict loan approval based on applicant data. Includes a web interface for submitting loan applications and receiving predictions. Built with Python and Jupyter Notebook.

ML Project implementing decision trees, boosting and svm classification from scratch.

This repo contains exploratory data analysis and modeling code for employee churn prediction system.

Machine learning library for classification tasks

The objective of this project is to showcase the use of Machine Learning models to answer the question of loan default prediction based on certain parameters from the German bank dataset.

Integrative Biomechanical and Clinical Features Predict In-Hospital Trauma Mortality

Road Traffic Accident Severity: A Comparative Analysis

Credit Fraud Detection of a highly imbalanced dataset of 280k transactions. Multiple ML algorithms(LogisticReg, ShallowNeuralNetwork, RandomForest, SVM, GradientBoosting) are compared for prediction purposes.

Built machine learning algorithms to best predict the loan approval based on the customer past data and demographics.

This dataset include data for the estimation of obesity levels in individuals from the countries of Mexico, Peru and Colombia, based on their eating habits and physical condition. The data contains 17 attributes and 2111 records.

Spam Email Detection using Machine Learning Classifier Algorithms

Python project for Banknotes Analysis.

Built machine learning algorithms (Decision Tree Classifier, Random Forest Classifier & Support Vector Classifier) to best predict the credit card approval.

To create a system that effectively detects and prevents credit card fraud using machine learning techniques, ensuring the security of financial transactions and protecting customers from fraudulent activities.

Data Science - Support Vector Machine Work

Machine learning to predict which passengers survived the Titanic shipwreck