Sentiment Analysis of Lockdown in India During COVID-19:A Case Study on Twitter
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Updated
Nov 10, 2023 - Jupyter Notebook
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.
Fake News Detection using Machine Learning Algorithms and deploying using Flask
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 Sklearn's Passive Aggressive Classifier Model
Random data science projects
It is an NLP-based classifier for detecting Fake news and classifying each news as Fake or Real.
The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 150.
Fake News Detection Using Python
detecting fake new from bunch of news
Fake News Classifier with TfidfVectorizer
A Supervised Learning model, PassiveAggressiveClassifier is used for detecting Fake news from a data set.
Implemented online learning algorithms which enable model updates with new data without full retraining.
Fake news detection using machine learning
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