IMDB ML-Model Flask Deployment

Project Overview

This project deploys a Machine Learning model to predict the sentiment of movie reviews using a Flask web application. Users can input movie details via a web GUI or API calls and get the predicted sentiment.

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Project Structure

The project consists of five main components:

1. imdb.py
   Contains the Machine Learning model code to predict sentiment based on training data from the IMDB.csv file.

2. app.py
   Flask application that exposes APIs. It receives movie details, computes the predicted sentiment using the model, and returns the result.

3. templates & static folder

   • templates contains the HTML templates for the web interface.
   • static contains CSS, JS, and other static files.
     Users can enter movie details and view predicted sentiment through these templates.

4. rdb
   SQLite database file used by Flask via Flask-SQLAlchemy to store movie reviews and predictions.

5. svm.pkl and tfidf.pkl
   Pickled files containing the trained SVM model and TF-IDF vectorizer, used for sentiment prediction.

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Running the Project

1. Setup

   • Unzip the project folder to your local system.
   • Make sure Python and required packages (Flask, scikit-learn, pandas, etc.) are installed.

2. Start Flask API

   python app.py