coderpriya Goto Github PK

-fake-news-detection-

Fake news is misinformation or manipulated news that is spread across the social media with an intention to damage a person, agency and organisation. Due to the dissemination of fake news, there is a need for computational methods to detect them. Fake news detection aims to help users to expose varieties of fabricated news. To achieve this goal, first we have taken the datasets which contains both fake and real news and conducted various experiments to organize fake news detector. We used natural processing, machine learning and deep learning techniques to classify the datasets. We yielded a comprehensive audit of detecting fake news by including fake news categorization, existing algorithms from machine learning techniques. In this project, we explored different machine learning models like Naïve Bayes, K nearest neighbors, decision tree, random forest and deep learning networks like Shallow Convolutional Neural Networks (CNN), Deep Convolutional Neural Network (VDCNN), Long Short-Term Memory Network (LSTM), Gated Recurrent Unit Network (GRU), Combination of Convolutional Neural Network with Long Short-Term Memory (CNN-LSTM) and Convolutional Neural Network with Gated Recurrent Unit (CNN-LSTM).

2014

Official content for the Fall 2014 Harvard CS109 Data Science course

2014_data

Data directory for the CS109 Data Science course

2015lab3

2016-10-facebook-fact-check

Data and analysis for the BuzzFeed News article, "Hyperpartisan Facebook Pages Are Publishing False And Misleading Information At An Alarming Rate."

2017-12-fake-news-top-50

Data and analysis supporting the BuzzFeed News article, "These Are 50 Of The Biggest Fake News Hits On Facebook In 2017," published on Dec. 28, 2017

2017spring

Deep Learning (for Computer Vision) Module - Spring 2017

2018-12-fake-news-top-50

Data and analysis supporting the BuzzFeed News article, "In Spite Of Its Efforts, Facebook Is Still The Home Of Hugely Viral Fake News" published on Dec. 28, 2018

2018ht12159_assignment1

2019-cs109a

https://harvard-iacs.github.io/2019-CS109A/

2019-cs109b

a2a-challenge

Machine Learning - Python - Cluster-first/Route-second strategy for the Vehicle Routing Problem

adnanaziz.github.io

Adnan's home page

adv_fin_ml_exercises

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

algorithm-implementations

Share, discuss and learn about algorithm implementations!

algorithms

Data Structures and Algorithms in Python

algorithms-1

Algorithms & Data Structures in C++

algoworks

alns

Adaptive large neighbourhood search (and more!) in Python.

amazonemployeeaccess

Design an algorithm to accurately predict the access status to certain resources of employees

arc

The Abstraction and Reasoning Corpus

arkcase

Case management and IT modernization platform.

ars

automl

Google Brain AutoML

awesome-ai-ml-dl

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

awesome-data-engineering

A curated list of data engineering tools for software developers

awesome-java

A curated list of awesome Java frameworks, libraries and software. Inspired by awesome-python.

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

awesome-nlp

A curated list of resources dedicated to Natural Language Processing