ML.NET
language-ext
ML.NET | language-ext | |
---|---|---|
17 | 41 | |
8,895 | 6,235 | |
0.6% | - | |
9.0 | 9.6 | |
4 days ago | 11 days ago | |
C# | 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.
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!
language-ext
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The Monad Invasion - Part 2: Monads in Action!
You probably noticed that .SetName() returns a Either. You may have come across Unit in libraries like MediatR or Language-Ext. It's a simple construct representing a type with only one possible value. We use it as a placeholder for operations that do not return a value but may return another state. In our example, .SetName() is a Command that does not return a value but may fail. Therefore, the monad Either carries two possible states: Right (without value) or Left (with an Error).
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The Monad Invasion - Part 1: What's a Monad?
Language-Ext is my personal favourite, but it can be a bit overwhelming for beginners due to its extensive feature set
- Why don't you just use F#?
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The combined power of F# and C#
> but I just want something closer to Scala, but for .Net
That's what I'm working toward with my language-ext library [1]. Obviously more support for expression based programming would be welcome (and higher kinds), but you can do a lot with LINQ and a good integrated library surface.
[1] https://github.com/louthy/language-ext
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Option<T> monad for Unity/UniTask
Definitely a fan of option types, I wonder this library has anything over the C# library language-ext which also has an Option type?
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Result pattern: language-ext vs FunctionalExtensions?
Hey, I am considering adopting the Result pattern in my codebase. Wanted to get some opinions from someone who has experience with it: should I start with language-ext or FunctionalExtensions?
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John Carmack on Functional Programming in C++ (2018)
> [1] https://github.com/louthy/language-ext
Cool library. I've had a few of these patterns in my Sasa library for years, but you've taken it to the Haskell extreme! Probably further than most C# developers could stomach. ;-)
You might be interested in checking out the hash array mapped trie from Sasa [1]. It cleverly exploits the CLR's reified generics to unbox the trie at various levels which ends up saving quite a bit of space and indirections, so it performs almost on par with the mutable dictionary.
I had an earlier version that used an outer struct to ensure it's never null, similar to how your collections seem to work, but switched to classes to make it more idiomatic in C#.
I recently started sketching out a Haskell-like generic "Deriving" source generator, contrasted with your domain-specific piecemeal approach, ie. [Record], [Reader], etc. Did you ever try that approach?
[1] https://sourceforge.net/p/sasa/code/ci/default/tree/Sasa.Col...
[2] https://sourceforge.net/p/sasa/code/ci/57417faec5ed442224a0f...
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Don't sleep on Linq query syntax if you regularly iterate through large/complex data sources
languageext supports linq for its monads and I kinda love it. The challenge is convincing my colleagues. 😅
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What C# feature blew your mind when you learned it?
language-ext supports it and it's pretty dang cool.
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It's actually not that bad...
I can only recommend c# language extensions library https://github.com/louthy/language-ext
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#.
OneOf - Easy to use F#-like ~discriminated~ unions for C# with exhaustive compile time matching
Accord.NET
CSharpFunctionalExtensions - Functional extensions for C#
FaceRecognitionDotNet - The world's simplest facial recognition api for .NET on Windows, MacOS and Linux
Optional - A robust option type for C#
OpenCvSharp - OpenCV wrapper for .NET
MoreLINQ - Extensions to LINQ to Objects
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.
Curryfy - Provides strongly typed extensions methods for C# delegates to take advantages of functional programming techniques, like currying and partial application.
Deedle - Easy to use .NET library for data and time series manipulation and for scientific programming
VisualFSharp - The F# compiler, F# core library, F# language service, and F# tooling integration for Visual Studio