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Fake News Detection

The main aim of this project is to detect the fake and real news using various Machine learning algorithim with NlP techinques for detecting the 'fake news',that is misleading news stories that comes from the non reputable sources.

Steps Involved

1.Importing the required packages into python environment.

2.Importing the dataset (Fake News.CSV and True News.CSV Dataset).

3.Preprocessing of data as required.

4.Exploratory Data Analysis (EDA) to extract features from the dataset.

5.Training of dataset using four machine learning classification algorithms and evaluate the trained model using evaluation metrics.

Data Modeling

Model is trained using four classification algorithms namely Logistic Regression, Random Forest Classifier, SVM and decision Tree Classifier. With these algorithms, the models are trained successfully and evaluate each of the model to find the most suitable model for this problem.

From this, I consider that DecisionTreeClassifier is one of the most suitable model as it gives accuracy of about 99.07% among all the classification algorithms.

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