Praveen76 / Build-a-Custom-NER-Model-using-Spacy

Build a Custom NER Model using Spacy

This repository contains code for building a custom Named Entity Recognition (NER) model using the spaCy library. The Medical NER dataset has been utilized for this experiment.

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Table of Contents

• Introduction
• Learning Objectives
• Usage
• Contributing
• License

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Introduction

Named Entity Recognition (NER) is a crucial task in natural language processing (NLP) that involves identifying named entities such as persons, organizations, locations, etc., in a text. In this project, we explore how to build a custom NER model using the spaCy library. We utilize the Medical NER dataset for training the model.

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Learning Objectives

At the end of the experiment, you will be able to:

• Understand the spaCy library
• Train a custom Named Entity Recognition (NER) model using spaCy

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Usage

Running the Notebook Locally

To run the notebook locally on your machine, follow these steps:

1. Clone this repository:

   git clone https://github.com/Praveen76/Build-a-Custom-NER-Model-using-Spacy.git
   

2. Navigate to the repository directory:

   cd Build-a-Custom-NER-Model-using-Spacy
   

3. Open the notebook file Build-a-Custom-NER-Model-using-Spacy.ipynb using Jupyter Notebook or JupyterLab.

4. Make sure you have all the required dependencies installed. You can install them using the following command:

   pip install -r requirements.txt
   

5. Execute the notebook cells one by one to understand the spaCy library and train the custom NER model.

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Running the Notebook on Google Colab

You can also run the notebook directly in your browser using Google Colab. Click the "Open in Colab" badge above, and it will open the notebook in Colab. Follow the instructions in the notebook to execute the cells and train the custom NER model.

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Contributing

Contributions are welcome! If you find any bugs or have suggestions for improvement, feel free to open an issue or create a pull request.

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License

This project is licensed under the MIT License.

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Credits

• This project is created and maintained by Praveen Kumar.

Issues:

If you encounter any issues or have suggestions for improvement, please open an issue in the Issues section of this repository.

Contact:

The code has been tested on Windows system. It should work well on other distributions but has not yet been tested. In case of any issue with installation or otherwise, please contact me on Linkedin

Happy coding!!

About Me:

I’m a seasoned Data Scientist and founder of TowardsMachineLearning.Org. I've worked on various Machine Learning, NLP, and cutting-edge deep learning frameworks to solve numerous business problems.