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-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).

100-days-of-ml-code

100 Days of ML Coding

1topic-modelling-to-group-reviews-

2018-cs109a

Repository for CS109A Fall 2018

2020-cs109a

2020-s109a

abbreviation-list-english

An extensive abbreviations list in English for NLP studies

affect-in-tweets-using-deep-learning-techniques

alibi

Algorithms for explaining machine learning models

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

basic-data-science-projects

bert-sentiment-analysis-turkish

Sentiment Analysis with BERT in Turkish Tweets

bertilesentimentanaliz

BERT ile Sentiment Analizi

bunch_jmsacl_reference_interval

c-rank

canigoout

Türkiyedeki covid-19 önlemleri kapsamında alınan sokağa çıkma kısıtlamalarını kontrol eden minik bir uygulama

cheatsheets-1

Official Matplotlib cheat sheets

class_data

comprehensive-evaluation-of-multivariate-chaotic-time-series-using-neural-networks

Multivariate chaotic time series prediction, a popular research topic which is concerned with many disciplines (weather forecasting and predicting stocks), where the end goal is to predict the future of the time series based on past observations. Various neural networks has been proposed to forecast future values in time series data but existing methods are not comprehensively evaluated.

covid-19-data

Data on COVID-19 (coronavirus) confirmed cases, deaths, and tests • All countries • Updated daily by Our World in Data

covid-functional-cluster

Functional Cluster and Canonical Correlation Analysis of EU Countries by Number of Daily Deaths and Stringency Index During Covid-19 Pandemic

covid19-fda

A functional data analysis of Covid-19 data

cv_outlier

data-science--cheat-sheet

Cheat Sheets

decisiontrees_bookch

SOSYAL BİLİMLER İÇİN ÇOK DEĞİŞKENLİ İSTATİSTİKSEL ANALİZ: STATA, R VE SPSS UYGULAMALARI adlı kitabın sınıflandırma karar ağaçları bölümünün kodlarını içerir.

detecting-fake-profiles-on-social-media

eksiapi

Ekşi Sözlük API

eksisozluk

A command line program to get entries from http://eksisozluk.com

emr2023

Introduction to Responsible Machine Learning with examples in healthcare

expectation-maximization-algorithm-for-clustering