riscv-newop
A RISC-V new instruction discovery tool [Work in Progress] (by riscv-newop)
implicit
Fast Python Collaborative Filtering for Implicit Feedback Datasets (by benfred)
| riscv-newop | implicit | |
|---|---|---|
| 4 | 3 | |
| 15 | 3,783 | |
| - | 0.0% | |
| 0.0 | 3.7 | |
| over 3 years ago | almost 2 years ago | |
| Python | Python | |
| BSD 2-clause "Simplified" License | MIT 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.
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.
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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.
implicit
Posts with mentions or reviews of implicit.
We have used some of these posts to build our list of alternatives
and similar projects.
- Recommendation system integration
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Content-based Recommender System with Python
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.
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Tensorflow Recommender (TFRS) or Scikit-Surprise?
In that case, you are doing some form of collaborative filtering, though you can also add content-based filtering as additional features later. You can use either implicit or explicit feedback. I would suggest checking this package, and this tutorial. Let me know if you have any other questions.
What are some alternatives?
When comparing riscv-newop and implicit you can also consider the following projects:
matrix-factorization - Library for matrix factorization for recommender systems using collaborative filtering
TensorRec - A TensorFlow recommendation algorithm and framework in Python.
platform-sifive - SiFive: development platform for PlatformIO
libffm - A Library for Field-aware Factorization Machines
recommenders - TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
annoy - Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk