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omarnokia's Projects

algorithms icon algorithms

:computer: Data Structures and Algorithms in Python

awesome-courses icon awesome-courses

:books: List of awesome university courses for learning Computer Science!

basicgesturedetect icon basicgesturedetect

Android app that displays "Hello" or "World" based on accelerometer data and touch events

buildozer icon buildozer

Generic Python packager for Android and iOS

cs228-material icon cs228-material

Teaching materials for the probabilistic graphical models and deep learning classes at Stanford

deeplearning.ai-summary icon deeplearning.ai-summary

This repository contains my personal notes and summaries on DeepLearning.ai specialization courses. I've enjoyed every little bit of the course hope you enjoy my notes too.

dtw icon dtw

DTW (Dynamic Time Warping) python module

freecodecamp icon freecodecamp

The https://www.freeCodeCamp.org open source codebase and curriculum. Learn to code for free together with millions of people.

keystroke-dynamics-1 icon keystroke-dynamics-1

Biometrics using Keystroke Dynamics coded in Java [hasty/inaccurate/incomplete] (CS3052 Computer Security - Assignment)

pcc icon pcc

Resources for Python Crash Course, from No Starch Press.

sampling_from_svm icon sampling_from_svm

What does a Support Vector Machine think data looks like? There's a bayesian interpretation of SVMs, which allows you to think of fitting an SVM as a MAP estimator. We sample from the corresponding prior.

sensordatamanager icon sensordatamanager

Android Library for exporting/managing data from the Sensor Manager Library

stargan icon stargan

Official Implementation of StarGAN - CVPR 2018

strengthening-of-user-authentication-using-keystroke-dynamics icon strengthening-of-user-authentication-using-keystroke-dynamics

This project aims to provide an addition layer of security for mobile devices by strengthening the user authentication using Keystroke Dynamics. This behavioral authentication technique is used along with the existing PIN based authentication system. It extracts the users behavioral features such as pressure, speed, press time, flight time, finger touch size and feeds to a Artificial Neural Network. The Neural Network makes use of Error Back propagation Algorithm to train the network with the features extracted during the training phase. During the testing phase it uses the input features to classify a user as legitimate or fake based on the adjusted weight vectors.

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