https://github.com/joaoassalim/class-by-description-classifier-with-nlp

Enhancing Item Classification through Natural Language Processing: Leveraging Text Descriptions for Precise Categorization
https://github.com/joaoassalim/class-by-description-classifier-with-nlp

bert fine-tuning nlp nlp-machine-learning scikit-learn sklearn tensorflow

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Enhancing Item Classification through Natural Language Processing: Leveraging Text Descriptions for Precise Categorization

• Host: GitHub
• URL: https://github.com/joaoassalim/class-by-description-classifier-with-nlp
• Owner: JoaoAssalim
• License: gpl-3.0
• Created: 2023-12-20T17:50:33.000Z (about 1 year ago)
• Default Branch: master
• Last Pushed: 2024-07-05T02:07:45.000Z (6 months ago)
• Last Synced: 2024-07-05T14:45:32.975Z (6 months ago)
• Topics: bert, fine-tuning, nlp, nlp-machine-learning, scikit-learn, sklearn, tensorflow
• Language: Jupyter Notebook
• Homepage:
• Size: 12.9 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Text Classification Project

## Overview

This project focuses on the classification of items based on their descriptions using Natural Language Processing (NLP) techniques. The goal is to leverage machine learning classifiers to automatically categorize items into predefined classes, including real estate, machinery, services, information technology, and furniture.

## Introduction

In our daily lives, the task of classifying diverse items into distinct categories is a common challenge that spans various industries. This project addresses this challenge by employing Natural Language Processing (NLP) techniques for text classification. The primary objective is to develop a model capable of accurately categorizing items into predefined classes based on their textual descriptions.

## Project Structure

- **`data/`**: Stores the dataset used for training and evaluation.

- **`notebooks/`**: Jupyter notebooks for experimentation and analysis.

## Requirements

- Python 3.9

- Required Python packages can be installed using: `pip install -r requirements.txt`

## Installation

1. Clone the repository:

   ```bash

   git clone https://github.com/JoaoAssalim/Class-by-Description-Classifier-with-NLP.git

   ```

## Available Implementations

This repository includes three different approaches for implementing the model:

- **`Sklearn`**: Implementation using traditional machine learning libraries.

- **`TensorFlow`**: Implementation using TensorFlow for building and training neural network models.

- **`Fine-tuning BERT`**: Implementation using the pre-trained model noneuralmind/bert-base-portuguese-cased for fine-tuning in Portuguese.

## Contributing

Contributions are welcome! If you'd like to contribute to this project, please fork the repository and submit a pull request.