Machine Learning Project

This repository contains the code and resources for a machine learning project focused on multi-label text classification. The project involves preprocessing text data, vectorizing the text, preparing tags, training a multi-label classifier, and evaluating the model's performance.

Project Structure

The project is organized into the following sections:

1. Data Preprocessing

• Importing necessary libraries
• Loading and cleaning the text data
• Text vectorization using CountVectorizer
• Preparing tags for multi-label classification

2. Model Training

• Training a multi-label classifier using Naive Bayes algorithm
• Predicting labels for the test dataset
• Evaluating the model's performance using Hamming Loss and Precision

Files

• main_notebook.ipynb: Jupyter notebook containing the code for the machine learning project.

Usage

To use this project, simply clone the repository and run the Jupyter notebook main_notebook.ipynb in a Jupyter environment.