youtube_popularity_prediction's Introduction

YouTube Video Popularity Predictor

Overview

This project aims to predict the popularity of YouTube videos in the AI and ML niche using machine learning and NLP techniques. The output is the predicted popularity

Dataset

The dataset consists of video titles, channels, views, likes, and other metrics from YouTube.

Setup and Installation

Clone this repository.
Install required packages: pip install -r requirements.txt
Start the Flask application by running: python run.py
Open your web browser and enter the URL http://127.0.0.1:5000 to access the application.

Structure

Youtube_Prediction/
- │
- ├── .flaskenv                   (Environment variables for Flask)
- ├── app/                        (Flask application directory)
- │   ├── __init__.py             (Initializes the Flask app and includes create_app function)
- │   ├── routes.py               (Contains route definitions for the Flask app)
- │   ├── templates/              (HTML templates for the application)
- │   │   ├── index.html          (The main page of the web app)
- │   │   └── result.html         (The page to display predictions or results)
- │   └── static/                 (Static files like CSS, JavaScript, and images)
- │       └── style.css           (CSS styles for the web app)
- │
- ├── model/                      (Directory for the machine learning model)
- │   ├── pre_processing.py       (Contains the Preprocessor class for data preprocessing)
- │   └── model.py                (Script to train and save the ML model)
- │
- ├── dataset/                    (Dataset directory) 
- │   └── AI_ML_YT_Videos.csv     (Dataset used by the ML model)
- │
- ├── run.py                      (Script to run the Flask application)
- ├── trained_model.pkl           (The trained machine learning model (saved after training))
- └── requirements.txt            (File specifying the dependencies for the project)