Top 13 Python recommender-system Projects
-
-
-
SonarQube
Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.
-
Although CF methods also have some explainability available. CF library https://github.com/benfred/implicit which I used a lot in my past projects, e.g. has the method model.explain available for that.
-
-
-
Transformers4Rec
Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.
Project mention: Show HN: Transformers4Rec -a new library for Transformers on Recommender Systems | news.ycombinator.com | 2021-09-29 -
Project mention: Observe differences in the behavior of recommendation models using RecBole | dev.to | 2022-01-05
Now, let's continue to try out RecBole on another data set, the second one being FourSquare NYC. I quote the description from https://github.com/RUCAIBox/RecSysDatasets ↓
-
Scout APM
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
-
Project mention: Show HN: RexMex – A Recommender Systems Evaluation Metrics Library | news.ycombinator.com | 2022-01-04
-
Project mention: A new way to build decentralised recommendation engines for the creator economy | news.ycombinator.com | 2021-12-25
Hear me out on what I think a truly decentralised content curation.
Twitter, FB (Meta), Youtube everyone harvests user data and train their recommendation engines which are then monetised by them (often unfairly).
In the future, the data stays on the users' devices and anyone can train their models by asking the user for the consent. THe data never leaves the device and ML models get trained on user device itself. The users get to choose from a host of recommendation choices and can ask for payment in return for using their data. So no one party can build a monopoly over the platform.
Check out a cool project I have been working on to solve this https://github.com/NimbleEdge/RecoEdge
-
You appear to have picked one part of a larger package and tried to use it as a plot program. If you look at Histogram.py you will see that it doesn't plot anything. It says:
-
matrix-factorization
Library for matrix factorization for recommender systems using collaborative filtering
Project mention: Recently launched my first end-to-end ML app! A film recommender system based on matrix factorization, built for Letterboxd users. | reddit.com/r/learnmachinelearning | 2021-02-26I originally tried using RiverML, which is dedicated to online ML, but after a ton of tweaking I still wasn't satisfied. In the end, I used the matrix-factorization library, which is not at all flashy but worked much, much better. By adjusting the learning rate and epochs for feeding new ratings into the model I can adjust how "personalized" the ratings are, and after a few days of messing with it I got it where I wanted it.
-
mtgbot
A Magic: The Gathering Finance Bot that generates excel spreadsheets of analyzed card values over a period of days given single MTGGoldfish.com cards or set/format lists for M:TG.
The code and instructions can be found here on my github: https://github.com/VanZandtr/mtgbot
-
movie-recommender
Movie recommender system based on Non-Negative Matrix Factorization and Singular Value Decomposition, with a Flask web interface (by lorenanda)
Project mention: 4 tips for creating an impressive data science portfolio on GitHub | dev.to | 2021-06-06For example, for my research project on psych-verbs I wrote a paper-like README targeted at academics/fellow linguists, whereas for my movie recommender system I wrote an informal short description and included a screencast, aimed at a general audience.
Python recommender-system related posts
- Content-based Recommender System with Python
- A new way to build decentralised recommendation engines for the creator economy
- Python Command not giving any output!
- Python Command not giving any output!
- Magic Finance Trending Bot Personal Project
- Recently launched my first end-to-end ML app! A film recommender system based on matrix factorization, built for Letterboxd users.
- Tensorflow Recommender (TFRS) or Scikit-Surprise?
Index
What are some of the best open-source recommender-system projects in Python? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | LightFM | 3,904 |
| 2 | spotlight | 2,603 |
| 3 | implicit | 2,591 |
| 4 | TensorRec | 1,171 |
| 5 | fastFM | 958 |
| 6 | Transformers4Rec | 394 |
| 7 | RecSysDatasets | 242 |
| 8 | rexmex | 142 |
| 9 | RecoEdge | 55 |
| 10 | riscv-newop | 13 |
| 11 | matrix-factorization | 8 |
| 12 | mtgbot | 5 |
| 13 | movie-recommender | 3 |
Are you hiring? Post a new remote job listing for free.
