matrix-factorization VS riscv-newop

Compare matrix-factorization vs riscv-newop and see what are their differences.

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)
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matrix-factorization riscv-newop
1 4
19 15
- -
2.9 0.0
6 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.

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.

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!
    2 projects | /r/learnpython | 11 Jul 2021
    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:
    2 projects | /r/learnpython | 11 Jul 2021
    2 projects | /r/Python | 10 Jul 2021
    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.
    2 projects | /r/Python | 10 Jul 2021

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.

implicit - Fast Python Collaborative Filtering for Implicit Feedback Datasets

platform-sifive - SiFive: development platform for PlatformIO

fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production

spotlight - Deep recommender models using PyTorch.

recommenders - TensorFlow Recommenders is a library for building recommender system models using TensorFlow.

LT-OCF - LT-OCF: Learnable-Time ODE-based Collaborative Filtering, CIKM'21

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.