This project uses machine learning to classify breast cancer tumors as malignant or benign using the Breast Cancer Wisconsin (Diagnostic) Dataset.

Supervised learning project using Gradient Boosting Classifier

Applying Supervised learning techniques on data to help CharityML identify people most likely to donate to their cause.

Udacity DataScience nanodegree classification problem

Finding Donor for CharityML - Machine Learning Nanodegree from Udacity

This project detects spam messages in SMS, including those written in regional languages typed in English. It uses an extended SMS dataset and applies the Monte Carlo method with various supervised learning algorithms to improve spam detection.

Model to Predict if a customer will purchase a Travel Package

Finding Donors with Machine Learning ( Support Vector Machine, Gradient Boosting Classifier, Random Forest Classifier )

Explore an ML model with Logistic Regression, SVM, Gradient Boosting, Random Forest, and Decision Tree, enhanced via Hyperparameter Tuning. Experience our GUI-based ML model with 82.49% accuracy. Try it now!

This research goal is to build binary classifier model which are able to separate fraud transactions from non-fraud transactions.