Learning scalability on cryptography app
This is a demo project that showcases the use of natural language processing techniques to generate text.
To get started with this project, you will need to have the following installed:
- Python 3.x
- Jupyter Notebook
The following Python libraries:
- spaCy
- NLTK
- TensorFlow
- PyTorch
- Clone this repository to your local machine.
- Open Jupyter Notebook.
- Navigate to the cloned repository and open the demo.ipynb file.
- Follow the instructions in the notebook to run the various sections of the demo.
The project is organized as follows:
demo-project/
├── data/
│ ├── input/
│ └── output/
├── models/
│ ├── spacy/
│ ├── nltk/
│ ├── tensorflow/
│ └── pytorch/
├── src/
│ ├── spacy/
│ ├── nltk/
│ ├── tensorflow/
│ └── pytorch/
├── demo.ipynb
└── README.md
The data directory contains input and output data. The models directory contains saved models, and the src directory contains source code for the various natural language processing techniques used in the project.
If you would like to contribute to this project, feel free to submit a pull request or open an issue.