matrix-factorization
Library for matrix factorization for recommender systems using collaborative filtering (by Quang-Vinh)
riscv-newop
A RISC-V new instruction discovery tool [Work in Progress] (by riscv-newop)
| matrix-factorization | riscv-newop | |
|---|---|---|
| 1 | 4 | |
| 19 | 15 | |
| - | - | |
| 2.9 | 0.0 | |
| 7 months ago | over 1 year ago | |
| Python | Python | |
| MIT License | BSD 2-clause "Simplified" License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
matrix-factorization
Posts with mentions or reviews of matrix-factorization.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-02-26.
-
Recently launched my first end-to-end ML app! A film recommender system based on matrix factorization, built for Letterboxd users.
I 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.
riscv-newop
Posts with mentions or reviews of riscv-newop.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-07-11.
-
Python Command not giving any output!
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:
From what i see, the histogram.py file only declares the class but doesn't execute it. You want to use the __main__.py file which takes an argument as an input and executes the histogram class with it.
What are some alternatives?
When comparing matrix-factorization and riscv-newop you can also consider the following projects:
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.
platform-sifive - SiFive: development platform for PlatformIO
implicit - Fast Python Collaborative Filtering for Implicit Feedback Datasets
spotlight - Deep recommender models using PyTorch.
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
LT-OCF - LT-OCF: Learnable-Time ODE-based Collaborative Filtering, CIKM'21
recommenders - TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
matrix-factorization vs LightFM
riscv-newop vs platform-sifive
matrix-factorization vs implicit
riscv-newop vs spotlight
matrix-factorization vs fastapi
riscv-newop vs LightFM
matrix-factorization vs spotlight
riscv-newop vs d2l-en
matrix-factorization vs LT-OCF
riscv-newop vs recommenders
riscv-newop vs implicit