Shikhar Sakhuja's repositories
ScrapeGoogleAdTexts
Gets all the ad copies for political ads on Google
GRE-Words-of-the-Day
Sends top GRE words with their definitions and sentences along with mnemonics (learning aid) to memorize the words.
LabelingTool
Labeling tool for manually labeling our dataset on Political Advertisements.
ScrapeTwitterPolAds
Code for scraping political ads off Twitter.
Support-Vector-Machine
Images of digits classified using Multi-Class SVM
VR-Replication
Implementation of VR Replication in GoLang
TwitterCloneDS
Twitter clone using VR Replication to replicate back end.
docs
Documentation for Seattle Testbed (scroll down for README)
Feed-Forward-Neural-Networks
Implementation of Feed-Forward Neural Network Algorithm to classify hand-written images.
fuzzywuzzy
Fuzzy String Matching in Python
hedwig
PyTorch deep learning models for document classification
Online-Political-Ads-Analysis
This is the web page for the report "An Analysis of United States Online Political Advertising" released by the NYU group conducting research on Online Political Advertisements.
patch-detector
Implementation of vulnerability detection over all versions of a software repository based on a fix patch.
Person_reID_baseline_pytorch
Pytorch ReID: A tiny, friendly, strong pytorch implement of person re-identification baseline. Tutorial 👉https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial
PlotNeuralNet
Latex code for making neural networks diagrams
PolAdsNLP
Some NLP stuff with the political advertisement text
shikhar394.github.io
Portfolio (forever under dev)
SIA
SIA is a data driven platform that recommends students on ideal career paths and graduate schools using information they wish to share.
StackADT
Implementation of a stack ADT using Array Stack and Array Deque to allow amortized constant time regular push, regular pop and pushing in the middle of the stack.
uptane
Reference Implementation and Demonstration code for Uptane
Week5_Lab
These are the required files for Lab in Week 5.
Week6_Lab
These are the required files for Lab in Week 6.