$wagm@nia (Rendezvous97)

Rendezvous97

Geek Repo

Company:@Pint-AI

Location:Bangalore

Home Page:https://www.pint-ai.com

Twitter:@Swagam_Dasgupta

Github PK Tool:Github PK Tool

$wagm@nia's repositories

Empowering-Journalists

We believe that curbing this subset of fake news would involve providing the necessary tools to journalists and users who take the time to sift through trustworthy content. In this light, our solution is to devise a methodology and program to assist a journalist to identify if an image and associated title are trustworthy. The fundamentals of our approach are based on corroboration of news, i.e, the image must be used in credible news websites with text similar to that of the associated title for the image and text to be reliable. If not, we recommend that the journalist (or user) perform a human verification procedure.

Language:PythonStargazers:2Issues:0Issues:0

Backpropagation_implementation

This repo. implements the backpropagtion algorithm widely used in Machine Learning. The user inputs the number of hidden neurons while the algorithm trains the Neural Network on the created model and the training dataset. Finally, the the machine predicts the outcomes on the testing dataset and plots the associated loss.

Language:PythonLicense:MITStargazers:0Issues:0Issues:0

CNN_Chars74k

Implementing variations of Convolutional Neural Networks using the Chars74k dataset.

Language:Jupyter NotebookLicense:MITStargazers:0Issues:0Issues:0

Computer-Vision-Basics

Fundamental tutorials to understand the basics of Image Processing and Computer Vision

Language:Jupyter NotebookStargazers:0Issues:0Issues:0
Language:JavaScriptLicense:MITStargazers:0Issues:0Issues:0

DeliveryCab

A basic delivery driver game that includes simple game mechanics—boosts, bumps & collisions.

Language:HTMLLicense:Apache-2.0Stargazers:0Issues:0Issues:0

Examining-Adversarial-Attacks-on-Image-Classification-Models

Current research on adversarial examples is largely focussed on deriving general defences against these attacks for all ML models irrespective of their architecture. In contrast to this methodology, we believe that each network architecture needs to be examined separately in order to make effective and specialized defensive capabilities. We must analyze the robustness of each architecture in isolation against different types of adversarial examples to understand the extent to which they are susceptible. Therefore, In this paper, we examine the extent to which Variational Auto-Encoders (Convolutional and Vanilla) and Convolutional Neural Networks (CNNs) are vulnerable to several gradient-based attacks on two types of datasets — high pixel density (Labelled Faces in the Wild dataset) and low pixel density (MNIST). Our aim is to review the confidence of each attack, its validity and hence, the degree of effectiveness of the attack taking place for both types of architectures. Additionally, we also examine the role siamese networks could potentially play in creating more secure and robust systems.

Language:Jupyter NotebookStargazers:0Issues:0Issues:0

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

Language:PythonLicense:BSD-3-ClauseStargazers:0Issues:0Issues:0

HTML101-Business-Card

A simple digital business card created during Scrimba's HTML & CSS course

Language:CSSLicense:MITStargazers:0Issues:0Issues:0

HTML101-Company-Website

A simple company website made post the Scrimba HTML & CSS course

Language:HTMLLicense:MITStargazers:0Issues:0Issues:0

HTML101-GIFt-Site

A simple site full of GIFs on hover made during Scrimba's HTML & CSS course

Language:HTMLLicense:MITStargazers:0Issues:0Issues:0

HTML101-Google-Clone

A simple static HTML & CSS Google Homepage Clone made during Scrimba's course

Language:CSSLicense:MITStargazers:0Issues:0Issues:0

HTML101-Hometown-Site

A basic site about Bengaluru for the finalproject of Scrimba's HTML & CSS course

Language:HTMLLicense:MITStargazers:0Issues:0Issues:0

HTML101-Personal-Site

A basic personal site with restricted information made during Scrimba's html & css course

Language:JavaScriptLicense:MITStargazers:0Issues:0Issues:0
Language:HTMLLicense:MITStargazers:0Issues:0Issues:0

Javascript-101

All projects developed to learn the basics of Javascript through Scrimba.

Language:CSSLicense:MITStargazers:0Issues:0Issues:0

JS101-Bball-Scoreboard

A simple basketball scoreboard with functionality made during Scrimba's JS course

Language:HTMLLicense:MITStargazers:0Issues:0Issues:0

JS101-Blackjack-Game

A simple version of the blackjack game made during Scrimba's JS course

Language:JavaScriptLicense:MITStargazers:0Issues:0Issues:0

JS101-Chrome-Extension

A simple chrome extension for lead tracking made during Scrimba's JS course

Language:JavaScriptLicense:MITStargazers:0Issues:0Issues:0

JS101-Emoji-Fighter

Basic random emoji selector game using JS made during Scrimba's JS course

Language:JavaScriptLicense:MITStargazers:0Issues:0Issues:0

JS101-Password-Generator

A random password generator created during Scrimba's JS course

Language:CSSLicense:MITStargazers:0Issues:0Issues:0

JS101-Unit-Converter

A simple unit converter made during Scrimba's Javascript basics course

Language:JavaScriptLicense:MITStargazers:0Issues:0Issues:0

Neural-Network-From-Scratch

Implementing an Artificial Neural Network based on Adrej Karpathy's Micrograd

Language:Jupyter NotebookLicense:MITStargazers:0Issues:0Issues:0

Polynomial_Estimator

This repo. contains the code to create polynomial estimators, additionally,

Language:Jupyter NotebookStargazers:0Issues:0Issues:0
Language:Jupyter NotebookLicense:MITStargazers:0Issues:0Issues:0

React101-Business-Card

A business card made in React

Language:JavaScriptLicense:MITStargazers:0Issues:0Issues:0

React101-React-Facts

A static page made using React during the Scrimba React course

Language:JavaScriptLicense:MITStargazers:0Issues:0Issues:0

Simple-Django-App

This is a simple Django app to test Model-Views-Templates structures as well as url mapping.

Language:PythonStargazers:0Issues:0Issues:0

Simple_Blog

A simple blog created on Django

Language:PythonStargazers:0Issues:0Issues:0

Simply_CRUD_App_Django

Trying out a few CRUD operations and template/model views.

Language:PythonStargazers:0Issues:0Issues:0