文件列表:

.ipynb_checkpoints/
Fake News Detection Model using Tensorflow.ipynb
LICENSE.md
archive.zip
fakenews.csv

# Fake News Detection Model with TensorFlow ## Overview This repository contains a Fake News Detection Model implemented using TensorFlow. The model is designed to classify news articles as either real or fake, based on the given input data. ## Features Utilizes TensorFlow for deep learning-based classification. Preprocessing scripts to clean and prepare the data. Easy-to-use training and evaluation scripts. Model inference script for making predictions on new data. ## Table of Contents Installation Usage Data Training Evaluation Inference Contributing License ### Installation To get started with the Fake News Model, follow these steps: Clone the repository: git clone https://github.com/RonoAnalyst/fake-news-model-using-tensorflow.git cd fake-news-model-using-tensorflow Install the required dependencies: pip install -r requirements.txt ### Usage Requirements Python 3.x TensorFlow Other dependencies listed in requirements.txt ### Data The dataset used for training the model should be placed in the data/ directory. Ensure that your dataset follows the required format (provide details or sample data). ### Training To train the Fake News Detection Model, use the following command: python train.py --epochs --batch_size Adjust the number_of_epochs and batch_size according to your training preferences. ### Evaluation Evaluate the model on the test set using: python evaluate.py ### Inference Make predictions on new data using the inference script: python inference.py --input ### Contributing Contributions are welcome! Please follow our Contribution Guidelines before submitting pull requests. ### License This project is licensed under the MIT License. # fake-news-model-using-tensorflow

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