This project focuses on detecting fraudulent payment transactions using machine learning techniques.

In this repository, we explored the topics of Logistic Regression, SVM and also some of the Deep learning techniques.

Spam email detection using Logisitic Regression Model and TF-IDF Vectorizer for Feature extraction. Integration for different Email providers (GMAIL,OUTLOOK,YAHOO) by connecting to IMAP server , classifying unseen Emails and storing marked emails as Spam in Junk/Spam folder.

Detection of Diabetic Retinopathy using Retina Images. Filtering on images using Gaussian Blur, using KNN PCA for dimensionality reduction and classification of healthy retina image from unhealthy. Different algorithms like KMeans and Logistic regression used for classification of retina image into one of the five classes.

Machine Learning Model to predict surviver in RMS Titanic using Logisitc Regression and kaggle dataset

The Diabetes Prognosis and Risk Assessment System is a comprehensive machine learning application that predicts diabetes risk levels based on 21 health indicators.

A python repository for Supervised Machine Learning examples and projects. Will be continuously updated.

Binary classification problem to predict whether a pair of questions are duplicates or not.

End to end NBA Injury Predictor with 4.78M record dataset, XGBoost, Random Forest, TensorFlow Neural Network, & Logistic Regression w/ 69% ROC-AUC. Built w/ serverless AWS Lambda deployment, S3 storage, Tableau dashboards & machine learning pipeline using Python, scikit-learn, TensorFlow, SMOTE class balancing & temporal validation methodology.

Machine learning project aimed at classifying songs into multiple genres simultaneously. Created in Python with simple Angular frontend.