https://github.com/shaadclt/next-word-prediction-lstm
A Jupyter Notebook-based project for Natural Language Processing (NLP) that generates new text based on the input seed text using an LSTM-based neural network.
https://github.com/shaadclt/next-word-prediction-lstm
Last synced: 6 months ago
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A Jupyter Notebook-based project for Natural Language Processing (NLP) that generates new text based on the input seed text using an LSTM-based neural network.
- Host: GitHub
- URL: https://github.com/shaadclt/next-word-prediction-lstm
- Owner: shaadclt
- Created: 2023-10-25T16:49:43.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2023-10-25T17:33:02.000Z (almost 2 years ago)
- Last Synced: 2025-02-02T09:41:21.810Z (8 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 23 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Next Word Prediction using LSTM
A Jupyter Notebook-based project for Natural Language Processing (NLP) that generates text using an LSTM-based neural network.
## Overview
This project uses TensorFlow and Keras to build a text generation model. The model is trained on the text and can generate new text based on an input seed text.
## Prerequisites
Before you begin, ensure you have met the following requirements:
- Python (>= 3.6)
- TensorFlow
- Numpy
## Getting Started
1. Clone this repository:
```shell
git clone https://github.com/shaadclt/Next-Word-Prediction-LSTM.git
```
2. Download the Sherlock Holmes text data and place it in the root folder with the name `sherlock-holm.es_stories_plain-text_advs.txt`.
3. Install the required Python packages:
```shell
pip install tensorflow numpy
```
## Executing the Project
Open the Jupyter Notebook `next_word_prediction.ipynb` and run all steps.
## Project Structure
The project directory structure is as follows:
```
- nwp_model.h5 # The trained NLP model
- sherlock-holm.es_stories_plain-text_advs.txt # Sherlock Holmes text data
- next_word_prediction.ipynb # Jupyter Notebook
- README.md # This README file
```
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.