Sentiment Analysis of Lockdown in India During COVID-19:A Case Study on Twitter

Machine learning approach for fake news detection using Scikitlearn

How one can use binary classifiers, variational auto-encoder, TICA, PCA, distance and dihedral order parameters as CVs in context of pepsin-like aspartic proteases e.g. BACE1 and plasmepsin-II.

Learned to detect fake news with Python. We took a political dataset, implemented a TfidfVectorizer, initialized a PassiveAggressiveClassifier, and fit our model. We ended up obtaining an accuracy of 92.82% in magnitude.

This Python project detect fake and real news using PassiveAggressiveClassifier.

Used different types of machine learning classifiers such as Passive Aggressive, Extra Trees, Dummy Classifier to detect the DDos attack and compared the accuracies of the classifiers to determine the best out of the three.

Fake news related to the coronavirus pandemic has now become a huge problem since false information can lead to worry and concerns regarding the disease. It is not possible to perfectly detect fake news unless the news has been labelled fake or real. Therefore, I have taken this issue as my problem and have developed a project that can detect fa…

Fake News Detection using Machine Learning Algorithms and deploying using Flask

Fake News Detection using Sklearn's Passive Aggressive Classifier Model

It is an NLP-based classifier for detecting Fake news and classifying each news as Fake or Real.

Random data science projects

Fake News Detection Using Python

A Supervised Learning model, PassiveAggressiveClassifier is used for detecting Fake news from a data set.

detecting fake new from bunch of news

Fake News Classifier with TfidfVectorizer