US-2020-Election-Campaign-Youtube-Comments-Sentiment-Analysis-RNN-Bidirectional--lstm-Flask-Deployment

Scrapped Youtube Video Link

        y_channel1    =    'https://www.youtube.com/watch?v=uf3Ps5dHxrE'
        y_channel2    =    'https://www.youtube.com/watch?v=yGPfKkjDIts'
        y_channel3    =    'https://www.youtube.com/watch?v=RHISJrOODJ4'
        y_channel4    =    'https://www.youtube.com/watch?v=FdAh2HJ98WE'
        y_channel5    =    'https://www.youtube.com/watch?v=5mRXTO05Ihg'
        y_channel6    =    'https://www.youtube.com/watch?v=jFoTW91m2_8'
        y_channel7    =    'https://www.youtube.com/watch?v=9HnKFUNlcfY'
        y_channel8    =    'https://www.youtube.com/watch?v=ytc6VScJUcE'

Original Non Compressed HDF5 Model File LINK

Model file compressed because of larger size if you want original file download from below Link

https://drive.google.com/drive/folders/1_E970Ty_TAKFyjHkvptN_57LoiBqwTV8?usp=sharing

PROJECT GOAL
Project Motivation
Requirements Installation
File Section
Details of Variables
Technologies Used
License

PROJECT GOAL

This project is designed to Analyse and predict the sentiments of the data which is Scrapped from Top US youtube news channel using Natural Language Processing with Python, FLASK, HTML, SQL.

A highly comprehensive analysis with all data cleaning, exploration, visualization, vectorization all steps are explained in detail.

Project Motivation

The US president has a huge influence on people's lives both at home and abroad, so when the next election is held on 3 November, the outcome will matter to everyone. This inspired me to take up this project and just to see some insights what will be the reality regarding this Election

Requirements Installation

The Code is written in Python 3.7. 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.txt

File Section

The Python file has following sections:

1- Data Scrapping

2- Data Cleaning

3- Text Preprocessing

4- Keras Tokenization

5- RNN LSTM Modeling

Technologies Used

License

  https://opensource.org/licenses/MIT

DheerajKumar97/US-2020-Election-Campaign-Youtube-Comments-Sentiment-Analysis-RNN-Bidirect--lstm-Flask-Deployment