A Simple Way to Learn NLP: Using Code to Unlock Language
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This repository contains slides and code samples for using Python to implement some NLP related tasks.
The repository includes the implementation of the following parts:
- Regular Expressions (RegEx)
- Text Tokenization
- Text Processing and Visualization
- Gensim Text Processing
- Named Entity Recognition (NER)
Note
You can either follow the steps below for local installation or use the provided Docker image for a containerized environment.
These commands will set up an isolated environment and install all required packages for this project.
uv sync # installs all dependencies
Codes run on top of a Docker image, ensuring a consistent and reproducible environment.
Important
You will need to have
Dockerinstalled on your machine. You can download it from the Docker website.
To run the code, you will need to first pull the Docker image by running the following command:
docker pull abmhamdi/nlp
This may take a while, as it will download and install all necessary dependencies.
docker compose up -d starts the container in detached modedocker compose down tears down the containerServices can be run by typing the command docker compose up. This will start the Marimo on http://localhost:1357, and you should be able to use Python from within the notebook by starting a new Python notebook.
This project is licensed under the MIT License - see the LICENSE file for details.
Content type
Image
Digest
sha256:bfb4609d8…
Size
272.2 MB
Last updated
6 months ago
docker pull abmhamdi/nlp