m2cgen
filter
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m2cgen | filter | |
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8 | 18 | |
2,707 | 799 | |
0.6% | - | |
0.0 | 0.0 | |
6 months ago | over 1 year ago | |
Python | Go | |
MIT License | GNU General Public License v3.0 or later |
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
filter
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Querying and transforming object graphs in Go
Here’s Rob Pike’s (one of the original Go designers) attempt to “see what the hubbub is all about”: https://github.com/robpike/filter
- Future language enhancements to go
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Why Golang instead of Kotlin?
I find the language really solid but asking on r/golang is quite an adventure. It's extremely distant from go's spirit, the grammar is even more rich than Rust. Typical example: let, run, with, apply, and also - they all practically do the same but with a different scope of this and return value. Just looking at the flow API can get your head spinning. To illustrate how much it's completely the opposite of Go, see how Rob Pike pokes fun at map/filter and tells people they should not use it . I guess you can't force all developers to adhere to this mental model, but that's about it, but that's about it, technical arguments are irrelevant except for extremely niche concerns about memory and startup time
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Supporting the Use of Rust in the Chromium Project
I mean sure, let's praise the ergonomics of channels and the reliability of maps. As for datastructures, we already have datastructures at home . They just work fine. Nobody needs more than that because rob pike told us so
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Why isn’t Go used in AI/ML?
Go will never have a map/filter syntax, to the point rob pike even makes fun of it , do you really want to use it for that kind of domain ?
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State of Rust for web backends
Also since generators are mentioned I recently came across this rob pike moment, he implemented a reduce function that takes and returns all interface{} types and uses reflection to check if the call is valid at runtime - that's the most typical Go that can ever be written in 40 lines - all that to make the point that it's useless. Such a great spirit. https://github.com/robpike/filter
- Go 1.21 may have a clear(x) builtin and there's an interesting reason why
- What necessary packages or functions that Go doesn't have?
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Golang is so fun to write
A few points that stood out to me: error handling in Go is generally pretty good. It's much more performant compared to throwing exceptions and the high frequency of error handling helps a lot with debugging and avoiding unexpected errors. What you've described as "poor OOP'ish" is partly true, yes Go does poor OOP, because it doesn't try to do OOP. The language favours composition over inheritance. Strongly applying OOP concepts in Go is simply not using the language in its intended way. For implicit interfaces, it's completely fair that you don't like them, but it's not a disadvantage of the language. I for one find implicit interfaces very intuitive and feel it's the right way for it to be done. No function overloading and lack of ternary operations is absolutely intentional, both of these are overcome by writing more expressive code, which is not a bad thing. Similarly with no built in map/filter/find, these can be achieved using for-loops. Reference https://github.com/robpike/filter for Rob Pike's implementation of filter, stating in the readme that there's not much use for it and to just use for-loops instead. Last thing, enums are expressed using iota: https://go.dev/ref/spec#Iota
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Lies we tell ourselves to keep using Golang
> I didn't get that desire for purity that you gleaned from it.
'Folks who develop an allergic reaction to "big balls of mutable state without sum types" tend to gravitate towards languages that gives them control over mutability, lifetimes, and lets them build abstractions.'
This mutability argument is present throughout the article. Seems like nothing sans Rust or niche functional languages is enough.
> Nil pointer exceptions, for example, don't have to exist anymore..
The language most notorious for those is Java due to almost everything being passed via a nullable reference. When everything can be nullable, how can you know where to check for it? Go addresses this to an extent by explicitly separating pointers from values. Values are the default and cannot be nil, so the opportunity for null dereferences is greatly diminished. It's not a perfect solution, but it's not nothing either.
> and yet they do in Go because they couldn't be bothered to add sum types.
Damn those lazy Go devs!
> Its type system is barely a step above a dynamic language.
Turns out even a basic type system is a huge improvement over none. Just being able to restrict values to concrete types goes a long way.
> You have to write the same imperative looping code over and over because Rob Pike would rather just use a for loop than something mildly expressive like map or filter (https://github.com/robpike/filter).
There are arguments to be made either way, but I definitely agree generics (along with iterators) should have been there since day 1.
> Every function that does meaningful work is littered with if err != nil { return err }.
One big positive of this that I don't see in other languages is every `return` in a function must be on the start of a line. That is, every single exit path of a function is easily findable by visually scanning
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#.
Weaviate - Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Synapses - A group of neural-network libraries for functional and mainstream languages
ply - Painless polymorphism
R Provider - Access R packages from F#
go-onnxruntime - Unofficial C binding for Onnxruntime in Golang.
gorse - Gorse open source recommender system engine
nihongo
randomforest - Random Forest implementation in golang
go-funk - A modern Go utility library which provides helpers (map, find, contains, filter, ...)
gago - :four_leaf_clover: Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)
goonnx - Go language bindings for ONNX runtime