Face Recognition Flask App using OpenCV

The Facial Recognition Flask App to identify gender from images and videos using the Machine Learning model to classify the images, between Male and Female. The project uses SVM, Numpy, Pandas, Matplotlib, PIL, CV2, Sci-kit Learn.

This Project automates the process of right swiping on Tinder. It makes use of Selenium for python and Chrome Webdriver on which the code is run and automation operation operates.

This project is build using python and it can tell whether the passwords a user use has been pawned/leaked in the security breaches and attacks. It gives the number of times a password was hacked and suggests whether to change a passowrd or if it is a strong password which has not been pawned.

This project checks whether a patient has heart disease or not with accuracy of 93%. The classification on different categorical features and the ensemble model is used in this classification problem "Random Forest Classifier".

The project deals with the domestic convenience and educational services
- An Android application that will ask the user to upload the file he/she wants to get printed. Then the app will ask the format including margin, font, font size etc.

This project uses deep learning and feature engineering, using many categorical features to perfrom a binary classification to calculate whether the loan should be given to an applicant or not.