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It facilitates document organization, decision-making, and workflow automation.\n![Blue and Yellow Modern Data Analysis Presentation](https://github.com/MohammadMoataz2/X-rayGuardian/assets/123085286/72c445f7-eb90-40db-8a89-52613d4ac0c9)\n### Benefits\n\n- Efficient document categorization\n- Enhanced organization and accessibility of textual data\n- Improved decision-making processes\n- Automation of document classification tasks\n![image](https://github.com/MohammadMoataz2/X-rayGuardian/assets/123085286/6d199cd6-565b-4b59-ab6a-de4f8d0ab080)\n\n## Data Processing Pipeline\n\n### Technology Used\n- NLP (Natural Language Processing)\n- NLTK (Natural Language Toolkit)\n- TensorFlow\n- Pandas\n- Matplotlib and Seaborn\n\n![image](https://github.com/MohammadMoataz2/X-rayGuardian/assets/123085286/2f9bcb2e-0b4d-4d52-b3e5-da39a6c3a813)\n\n\n## Model Building\n\n### Technology Used\n- Deep Learning\n- TensorFlow Keras\n- Embedding Layers\n- LSTM (Long Short-Term Memory)\n- Adam Optimizer\n\n## Web Application\n\n### Technology Used\n- FastAPI\n- HTML/CSS\n- JavaScript\n- Python\n- File Handling Libraries\n- AJAX (Asynchronous JavaScript and XML)\n\n## How to Run\n\nTo run the application, follow these steps:\n1. Install the required dependencies listed in the requirements.txt file.\n2. Run the FastAPI server using the command: `python -m uvicorn main:app --reload`.\n3. Access the application by opening the index.html file in a web browser.\n\n## Contributions and Requirements\n\nContributions are welcome. Please refer to the project's GitHub repository for guidelines and requirements.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmohammadmoataz2%2Fdeeptextclassifier","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmohammadmoataz2%2Fdeeptextclassifier","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmohammadmoataz2%2Fdeeptextclassifier/lists"}