Merge pull request #1017 from Dharun235/fake-news-detect

Added the main code, readme and dataset folder

Machine_Learning/Fake news detection project/README.md

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+# Fake News Detection
+
+This project aims to create a machine learning model that detects fake news articles based on their content. It uses Natural Language Processing (NLP) and text classification techniques to classify news as either real or fake.
+
+## Dataset
+The dataset used is the [Fake and Real News Dataset](https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset) from Kaggle. 
+
+The dataset used consists of two CSV files:
+- `Fake.csv` contains fake news articles.
+- `True.csv` contains true news articles.
+
+Both files should be placed in the `dataset` directory and include the following columns:
+- **title**: The title of the news article.
+- **text**: The content of the news article.
+- **subject**: The subject/category of the news article.
+- **date**: The publication date of the news article.
+
+## Features
+
+- **TF-IDF Vectorization**: Converts text data to a format suitable for machine learning.
+- **Naive Bayes Classification**: A probabilistic classifier ideal for text-based tasks.
+
+## Requirements
+
+Install the required Python libraries:
+
+```bash
+pip install pandas numpy scikit-learn