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⚡ A text classification project that classifies news as Fake or Real using FastText.
ecommerce_dataset.csv)1├── .ipynb_checkpoints/ # Jupyter notebook checkpoints
2├── TextClassification.ipynb # Main notebook
3├── TextClassificationPart2.ipynb # Extended analysis notebook
4├── requirements.txt # Python dependencies
5├── .gitattributes # Git LFS configuration
6├── ecommerce.train # Training dataset (LFS)
7├── ecommerce.test # Test dataset (LFS)
8├── ecommerce_dataset.csv # Full dataset (LFS)
9└── README.md # Project documentation
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12⚙️ Setup Instructions
131️⃣ Install Dependencies
14pip install -r requirements.txt
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162️⃣ Run Training / Evaluation
17
18Open the Jupyter notebooks:
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20jupyter notebook TextClassification.ipynb
21jupyter notebook TextClassificationPart2.ipynb
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24Make sure to have datasets available locally (ecommerce.train, ecommerce.test, ecommerce_dataset.csv) or tracked via Git LFS.
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26🎯 Use Cases
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28Detect fake news in real-time applications
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30Build NLP portfolio projects
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32Experiment with FastText embeddings and text classification
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34💡 Future Improvements
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36Add real-time API for classification
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38Integrate with Hugging Face Datasets
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40Hyperparameter tuning for better accuracy
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42Add visualization dashboards for analysis
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44👨💻 Author
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46Vikas Gautam