m2cgen
ML.NET
Our great sponsors
m2cgen | ML.NET | |
---|---|---|
8 | 17 | |
2,707 | 8,838 | |
0.6% | 0.7% | |
0.0 | 8.9 | |
6 months ago | 1 day ago | |
Python | C# | |
MIT License | MIT License |
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.
m2cgen
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How to use python ML script in tauri?
Check out: https://github.com/BayesWitnesses/m2cgen
- EleutherAI announces it has become a non-profit
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Redis as a Database — Data Migration With RedisOM, RedisGears and Redlock
Notice that I’m using random values to populate the Sentiment field. You might compute the values for your fields based on other fields or actually use an ML model to perform the transformation. E.g. you could make use of m2cgen to transform trained models to pure python code and load them in **RedisGears **to be executed in a *GearsBuilder *instance. Another option is to pull out the big guns and go straight to RedisAI.
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Why isn’t Go used in AI/ML?
I wish that it was more common for model outputs to be converted the way bayeswitness does with mc2gen https://github.com/BayesWitnesses/m2cgen
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Use your decision tree model in your Javascript project today with m2cgen
And that’s it! All the magic in just two lines of code. I would like to thank the authors of the m2cgen library and encourage you to try it out.
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We use Rust for an opensource malware detection engine. It's great at detecting ransomwares and we want to share results and ideas with you.
I forgot to update the README. We just replaced RNN with xgboost that has a better f1 and is very quick, as the decision trees are translated to plain rust using m2cgen.
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Is data science/engineering in Rust practical, does it provide any benefit over Python, and what are the best crates?
Probably, as many frameworks come with a Rust support (or there are wrappers). Some models, like decision tree, can also be automatically translated to plain Rust (in my company we use m2cgen to translate xgboost models to plain rust code).
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Flutter Machine Learning App
These repositories on GitHub are good start I think: https://github.com/BayesWitnesses/m2cgen and https://github.com/vickylance/dart_nn
ML.NET
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ML.net image classification, poor GPU accuracy
You can direct your question to https://github.com/dotnet/machinelearning/issues. Perhaps it is already documented.
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Building a File Analysis Dataset with Python
Here I'm analyzing all projects in the src and test directories of the ML.NET repository. I chose to include these as separate paths because they represent two different groupings of projects in this repository.
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Extracting git repository data with PyDriller
Important Note: looping over repository commits takes a long time for large repositories. It took 52 minutes to analyze the ML.NET repository this code example refers to, which had 2,681 commits at the time of analysis on February 25th, 2023.
- Can we please be allowed to do machine learning object detection model training locally?
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ML.NET: can Microsoft's machine learning be trusted?
We checked the ML.NET 1.7.1 version. The source code of this project's version is available on GitHub.
- Stable Diffusion converted to ONNX (Demo usage, optimized to CPU)
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Why is there a lack of cool repos?
machine learning? https://github.com/dotnet/machinelearning
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what is the future of ML.NET?
You can follow some of our plans by taking a look at our roadmap which we'll be updating shortly to more accurately reflect the areas we're investing in.
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Does anyone actually use ML.NET?
Re: ONNX, if you run into similar issues in the future, feel free to reach out in our GitHub repo or the ONNX Runtime repo and we'd be happy to help!
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Requesting Senior Project Ideas
Good clarification, I think using something like ML.NET could be cool but I have some experience with Blazor that might be fun to use as well, I think generally performance monitoring or optimizing systems seems interesting to me, and I'm really open to other ideas as well. Let me know if any of that helps narrow my question down!
What are some alternatives?
TensorFlow.NET - .NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#.
Synapses - A group of neural-network libraries for functional and mainstream languages
Accord.NET
R Provider - Access R packages from F#
FaceRecognitionDotNet - The world's simplest facial recognition api for .NET on Windows, MacOS and Linux
gorse - Gorse open source recommender system engine
OpenCvSharp - OpenCV wrapper for .NET
randomforest - Random Forest implementation in golang
Catalyst - 🚀 Catalyst is a C# Natural Language Processing library built for speed. Inspired by spaCy's design, it brings pre-trained models, out-of-the box support for training word and document embeddings, and flexible entity recognition models.
gago - :four_leaf_clover: Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)
Deedle - Easy to use .NET library for data and time series manipulation and for scientific programming