Project Info
This project did not submit a demo video on Devpost.
Inspiration
Looking for hours for a movie to watch with seemingly no end to the random trailers in sight.
What it does
Muru curates a selection of movies based on your likes and dislikes based on an IMDb dataset that finds the cosine similarities between your inputs and other movies based on genres and keywords.
How we built it
Our website's front and backend were created through Reflex and our dataset was collected through IMDb.
Challenges we ran into
We had several issues connecting the front and back ends of our project together. Switching the webpage to the recommended movies page and printing out the five posters caused us the most trouble. We solved this issue by returning the movie poster and printing it in a grid. Figuring out how to create the recommendations was pretty difficult. None of us had any experience when it came to processing data. It required a lot of research to get started working on it. We ended up switching to a different project late Friday.
Accomplishments we're proud of
We are proud that we were able to create a proper project. We are proud to create a really good algorithm that recommends movies We are proud that we were able to work together to combine all our work
What we learned
We learned a lot about preparing ahead of time for projects. Some of us had to learn Python to use Reflex for our front and backend Learned how to utilize data. (extract/refine) Learned how to find similarities in datasets.
What's next
We want to implement a few features. An evil mode Our original plan was to include this as a fun bit to find movies you wouldn't like An exit/match feature This would allow more similarities for the Tinder UI Change how the frontend loads the movie recommendations/images This would increase the speed of the website Currently, it updates the whole website but we would want it to redirect the user Finnaly, we would want to have it hosted and running
Muru-The-Movie-Guru 1.0
Cal Hack 11 Submission
Tinder X Movies
- Uses an imdb movie dataset
- The code computes cosine similarity between different movies based on their genres and keywords to recommend movies based on user preferences. For liked and disliked movies, the system computes a similarity score, subtracting the disliked movie scores from the liked ones to generate a recommendation.
Analysis
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Metric
- 8
Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.
Technology
- PythonIn code
1 of 1 appear in the indexed code.
AI coding agents
No AI coding agent signals were found in this repository.
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Codebase size
Source size
24 KB
Source files
7
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Repository
ricardo-escalante06/Muru-The-Movie-Guru
10 files · 1.2 MB · @ 8fe8a3a
Structure
Application logic
7 files · 70%Domain rules, services and shared utilities.
Supporting
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Languages
- Python98%
- Markdown2%
Share of indexed source by file size. Binary and vendored files are excluded.
Dependencies
MovieTinder/requirements.txt
pypi · 1- reflex
Declared in the repository’s manifests at the indexed commit. A declared package is not proof it is used, and runtime dependencies are listed first.
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