Movie Recommendation 🎥

A collaborative filtering based recommendation engine!

Discover Your Next Movie Night Gem!
Tired of endless scrolling, trying to find the perfect movie? 🍿

Contents

• Introduction
  
• Future Project Plan
  
• Video
  
• Working
  
• Tech Stack
  
• Requirements and Setup
  
• Usage
  
• Documentation
  
• Bug
  
• License

Introduction 👁️

Say hello to our Movie Recommender! 🚀
Just tell us what type of movies you like, and we'll serve up a handpicked list of 10 must-watch movies tailored to your taste. No more movie-night dilemmas! 🎬
Save time, ditch the hassle, and let Movie Recommender do the work for you. Movie night has never been this easy and exciting! 🌟
Your perfect movie is just a click away. Get started now and make every movie night a hit! 👏

Future Project Plan 🔮

Testing how good the Movie Recommender is :

1. Enhanced Recommendation Algorithm: Use machine learning to personalize movie suggestions based on user ratings and feedback, improving accuracy over time.
2. User Community Features: Add social elements like reviews, comments, and recommendations based on what friends or community members are watching.
3. Integration with External APIs: Connect with movie databases like IMDb or TMDb to get real-time movie details, ratings, and trending films for a better user experience.
4. Watchlist Feature: Allow users to create a personalized watchlist by saving movies they are interested in.

Note: Our system can be virtually tested through Github Actions inbuilt feature of build and test queries using python.

Make sure you taste your own medicine first and take into account other peoples familiarity with the system before you design your tests.

Video ▶️

![Watch the video]

Working 📱

Below working displays the system also evaluates movie attributes such as genre, cast, director, and user-generated reviews.

• By combining these user-specific data and film characteristics, the recommender system employs machine learning to generate tailored movie recommendations.
• This enables users to discover new films that align with their individual tastes, making the movie-watching experience more enjoyable and engaging.
• The users can directly watch the trailer of any movie recommended to them.
• Furthermore, recommender systems often employ a feedback loop, where users' interactions and feedback help refine the recommendations over time, ensuring that the suggestions remain relevant.
• The users can register and log in to their accounts to keep a history of the movies recommended for them.

New Features

1. Register Page: Enhanced with password validation, ensuring it includes characters, numbers, and special characters.
2. Loading Spinner: Implemented a loading spinner between the predict and recommendation process for a smoother user experience.
3. Star-Based Rating System: Added a 5-star rating system for users to rate movies they’ve already watched.
4. Feedback Functionality: Enabled feedback options only when users select an option, ensuring interaction is required.
5. History Feature: The history page now displays only the movies for which users provided feedback.
6. Watchlist Feature: Allow users to create a personalized watchlist by saving movies they are interested in.

Tech stack 👨‍💻

Python

Python is a high-level, general-purpose programming language known for its simplicity and readability. It's a widely used language for web development, data analysis, artificial intelligence, and more.

Flask

Flask is a micro web framework written in Python. It's lightweight and easy to use for building web applications, making it an excellent choice for small to medium-sized projects.

HTML

HTML (Hypertext Markup Language) is the standard markup language for creating web pages and web applications. It's used for structuring the content on the web.

CSS

CSS (Cascading Style Sheets) is a style sheet language used for describing the look and formatting of a document written in HTML. It's essential for web design and layout.

JavaScript

JavaScript is a versatile and widely used programming language for adding interactivity and dynamic behavior to web pages. It's essential for client-side web development.

Requirements and Setup ⚙️

• python 3.5 +

• pip

• Style check - black pip install black

• Static code analyser - Pylance Install it in VS Code

• Install all required python packages pip install -r requirements.txt

Usage

1. cd Code/recommenderapp
2. python3 app.py

Documentation 📚

Refer to Wiki page here

Chat Channel 🗣️

Refer to our chats here

Bug? 🐛

Raise an issue on this repository, we would love to look at it ❤️

License 📃

This project is under MIT License.

• The MIT license explicitly grants users the right to reuse code for various purposes,hence for improval of future scope of the code we have added MIT license.
• They include the original MIT license when distributing it. Allowing users to customize or adapt the code to meet their specific requirements.