文件列表:

Fake.csv (62789876, 2023-10-21)
FakeNewsDetection.ipynb (55731, 2023-10-21)
True.csv (53561522, 2023-10-21)
manual_testing.csv (88020, 2023-10-21)

# FakeNewsDetection This is a python project on fake news detection. This project of detecting fake news deals with fake and real news. Using Sklearn, we build a TfidfVectorizer on our dataset. Then, we initialize a Passive Aggressive Classifier and fit the model. In the end, the accuracy score and the confusion matrix tell us how well our model works. #Project Prerequesites The dataset used in this project is true.csv and fake.csv. These data files can be downloaded from https://www.kaggle.com The environment used to run this project is jupyter notebook. Fake News Detection - Developed and implemented a machine learning-based fake news detection system to automatically identify and classify fake news articles and misinformation. - Utilized natural language processing (NLP) techniques to preprocess and analyze textual data. - Designed and trained machine learning models, including supervised and unsupervised learning algorithms, for fake news classification. - Implemented feature engineering and text vectorization to improve model accuracy. - Achieved an accuracy rate of 90% in detecting fake news articles, contributing to the fight against online misinformation. - Tools and Technologies: Python, scikit-learn, NLP libraries

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