- Demo
- Overview
- Motivation
- Installation
- Deployement on Heroku
- Directory Tree
- Bug / Feature Request
- Future scope of project
Link: https://twitter-sentiment-anaylsis.herokuapp.com/
This is a Flask web app that has a functionality to classify twitter tweets into positive, negative and neutral with the accuracy of 77.5%.
What to do when you are at home due to this pandemic situation? I started to learn about Machine Learning models and NLP to get most out of it. I came to know mathematics behind all supervised models. Finally it is important to work on application (real world application) to actually make a difference.
The Code is written in Python 3.9.2 If you don't have Python installed you can find it here. If you are using a lower version of Python you can upgrade using the pip package, ensuring you have the latest version of pip. To install the required packages and libraries, run this command in the project directory after cloning the repository:
pip install -r requirements.txtLogin or signup in order to create virtual app. You can either connect your github profile or download ctl to manually deploy this project.
Our next step would be to follow the instruction given on Heroku Documentation to deploy a web app.
├── static
├── bg.png
├──result.png
├── template
├── index.html
├── result.html
├── readme_resources
├── home.png
├── result1.png
├── README.md
├── app.py
├── transform.pkl
├── twitter_sentiment_analysis.ipynb
├── model.pkl
├── requirements.txt
├── Procfile
• If you find a bug (the website couldn't handle the query and / or gave undesired results), kindly open an issue here by including your search query and the expected result.
• If you encounter this webapp as shown in the picture given below, it is occuring just because free dynos for this particular month provided by Heroku have been completely used. You can access the webpage on 1st of the next month.
• Sorry for the inconvenience.
- Use multiple Algorithms
- Optimize Flask app.py
- Attractive Front-End