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albertoalonsohernan/Movie-Recommender

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App README

Movie-Recommender-AI

AI-powered movie recommendation system with content-based and collaborative filtering, built with Python and Streamlit.

The project implements different recommendation techniques, including Content-Based Filtering and Collaborative Filtering, with the objective of generating personalized movie recommendations through an interactive web interface.

Features of the project

  • —Movie recommendation based on content similarity
  • —Collaborative filtering using user ratings
  • —Interactive graphical interface
  • —Movie filtering by genre and rating
  • —Recommendation explanations
  • —Web deployment using Streamlit

Project objectives

  • —Develop a Content-Based Recommendation System
  • —Implement a collaborative Filtering Model
  • —Build an Interactive User Interface
  • —Apply Artificial Intelligence Techniques
  • —Use Software Engineering Best Practices
  • —Modular Arquitecture
  • —Clear documentation
  • —Version control with Git
  • —Deploy the Application

Technology Stack

  • —Python
  • —Pandas
  • —NumPy
  • —Scikit-Learn
  • —Streamlit
  • —Git & GitHub

Dataset

This project uses the MovieLens Latest Small dataset provided by GroupLens Research.

Project Roadmap

  • —[x] Phase 1: Project design and planning
  • —[x] Phase 2: Data collection and preprocessing
  • —[ ] Phase 3: Content-based recommender
  • —[ ] Phase 4: User interface development
  • —[ ] Phase 5: Collaborative filtering
  • —[ ] Phase 6: Integration and refinement
  • —[ ] Phase 7: Documentation and portfolio preparation
  • —[ ] Phase 8: Deployment

Installation

  1. 1.Clone the repository
bash
git clone https://github.com/albertoah9/Movie-Recommender-AI.git
  1. 1.Navigate to the project directory
bash
cd Movie-Recommender-AI
  1. 1.Install the dependencies
bash
pip install -r requirements.txt

Development Environment

Create a virtual environment:

bash
python -m venv env

Activate it:

bash
source env/bin/activate

Install dependencies:

bash
pip install -r requirements.txt

(Optional) Register the Jupyter kernel:

bash
python -m ipykernel install --user --name env --display-name "Python (env)"

Run the Streamlit App

bash
streamlit run app.py

Live Demo

Try the application online:

https://albertoah9-movie-recommender-ai-app-lyoiqd.streamlit.app