edgeml
rust
edgeml | rust | |
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1 | 9 | |
12 | 4,986 | |
- | 0.6% | |
0.0 | 5.2 | |
about 1 year ago | 5 months ago | |
Rust | Rust | |
- | Apache License 2.0 |
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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.
edgeml
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Newbie Rustacean... I participated in a hackathon at work building demos for WASM/WASI, and I got my demo publicly featured today. It uses tract for an ML inference engine. Such an ace OSS project, and way before I learned of wasi-nn 💖
Yes, using tract, which is a pretty awesome project! Check that out. I just wrote this simplistic demo last year, to test the capabilities of a serverless compute platform — it's all compiled to WebAssembly, running on a server, no binary to download, subject to resource constraints etc (repo if you're curious). ML is not my focus at all, and next I explore it again, it will be in the context of wasi-nn.
rust
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Have you ever wanted a library to check for 69 in a string?
You can use Tensorflow for Rust to simplify that task and avoid pain with regex. Just have the right mindset.
- Rust vs cpp for a new engineer to autonomous vehicles and robotics
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Making a better Tensorflow thanks to strong typing
What is the benefit of this compared to using bindings/a wrapper to Tensorflow, or other ML libraries written in C/C++, such as this community hosted project on tensorflow's github. If it's just for fun that is a valid enough reason imo, just curious since you describe it as a better Tensorflow because of the typing vs using the python wrapper, when there already exist ways to interact with tensorflow with both Rust and other statically typed languages, also including C++ (officially supported), C#, Haskell and Scala, as well as probably having bindings not mentioned on the documentation for more niche languages.
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Integrating machine learning models into Rust applications?
(3) You could use TensorFlow as your executor: https://github.com/tensorflow/rust
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Why Static Languages Suffer From Complexity
TensorFlow has language support for TypeScript well as Rust.
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Is PyO3 library production ready?
Thank you for the restponse! With tensorflow I am probably better of with something like; [tensorflow rust bindings](https://github.com/tensorflow/rust/tree/master/src). But I believe some useful extensions are still written in python for example; [TFDV](https://github.com/tensorflow/data-validation).. and how about scikit-learn or even something that is simpler like fb-prophet that is entirely written in python?
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How mature is the QT integration?
Tensorflow bindings exist, technically, but they're in a pretty rough state AFAIK.
- Feasibility of Using a Python Image Super Resolution Library in My Rust App
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Rusticles #10 - Wed Sep 09 2020
tensorflow/rust (Rust): Rust language bindings for TensorFlow
What are some alternatives?
tract - Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
leaf - Open Machine Intelligence Framework for Hackers. (GPU/CPU)
anyhow - Flexible concrete Error type built on std::error::Error
Rustup - The Rust toolchain installer
rusty-machine - Machine Learning library for Rust
solana - Web-Scale Blockchain for fast, secure, scalable, decentralized apps and marketplaces.
CNTK - Wrapper around Microsoft CNTK library
coreutils - Cross-platform Rust rewrite of the GNU coreutils
rustlearn - Machine learning crate for Rust
polkadot - Polkadot Node Implementation
rust-analyzer - A Rust compiler front-end for IDEs