Stack Overflow Tags Prediction

Predicting Tags Based on Stack Overflow Dataset

Table of Contents

• About the Project
• Getting Started
  • Prerequisites
  • Installation
• Predicting the Tags architecture
• Contributing
• License
• Contact

About The Project

Given a dataset that have Title, Body and Tags in the dataset, predict the Tags according to the title and body.

Getting Started

To get a local copy up and running follow these simple steps.

Prerequisites

Install the necessary packages in your own environment.

jupyter notebooks, Python 3.6, Scikit-Learn, Keras, Tensorflow, NLTK, WordCloud, pandas, Matplotlib, Seaborn

Installation

1. Clone the repo

git clone https:://github.com/FairozaAmira/Stack_Overflow_Tags_Prediction.git

2. Download the data from here.
3. Run the load_data.ipynb files to partition the data into smaller parts if you train it using Google Colaboratory or depending on your computing resources.
4. Run both other notebooks.

Predicting the Tags Architecture

1. Data analysis
2. Data preprocessing
3. Data cleaning
4. Predicting by using TF-IDF and Logistic Regression with OneVsRestClassifier
5. Predciting with LSTM and GRU models

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the Apache 2.0 License. See LICENSE for more information.

Contact

fairozaamira@gmail.com