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amazon-food-reviews-analysis-and-modelling

[Machine Learning | Data Analysis] Data Analysis on Amazon Fine Food Reviews dataset.

android-basics

ALL IN ONE : Calculator, Check if age > 18, Login/ Registration, Coin Flip, Contacts

assist-ans

A mobile-first grievances web-app using NLP

athena-virtual-classroom

carlelo

A car renting website

dominant-colors

Finds 'n' number of dominant colors in the image using K-Means Clustering

ebay-search-angular

ebay-search-chalogocartchalo

A webpage that allows users to search items for sale on eBay.com using their API

educoin

file-storage-script

gameofthrones

gt-crossview

Localizing and Orienting Street Views Using Overhead Imagery

hack-sc-macncheese

HackSC 2020

image_hashing

Perceptual hashing using dHash

krishi-sahayak

Mobile-first web application that can enable the farmers to contact an expert directly and make enquiries

ks

Testing

lbs-rpi

lionsclubofturbhe

looking-beyond-safety

Lane detection to find lane number for dynamic speed limit

lotion

✨ Smooth, easy blockchain apps ✨

ml-discussions

Jupyter notebooks for the ML course at UCI

my-first-blog

organ-donation

An Android Application for organ donation.

photogallery

Android Application rendering recent images from flickr

pix2pix-tensorflow

Tensorflow port of Image-to-Image Translation with Conditional Adversarial Nets https://phillipi.github.io/pix2pix/

poisoning_attack_perceptual_hash

Our project detects a hash poisoning attack, in which the poison image having the same hash of the innocent image is uploaded and causes a denial of service to the legitimate users trying to upload, but because it has the same hash as that of poison image, the system compares the hash with the hash table and deletes the innocent image. We aim to mitigate with the help of a counter associated with every hash which maps the hash collisions. If the count increases beyond threshold, system reviews the incoming image while removing the hash entry from the database. In the second phase, we take into consideration the poison images modified using steganography methods that transfers unwanted malicious files along with the image uploads. We use the message authentication mechanism incorporating the use of MD5 hash which is sent along with the image and is verified at the server side.

reminder

Reminder is a simple material design Android application to create reminders and notes.

todo

truffle-pet-shop

workshop