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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A work in progress to build out solutions in Rust for MLOPs
| Date | Stars |
|---|---|
| 2026-07-24 | 383 |
| 2026-07-25 | 383 |
| 2026-07-28 | 383 |
| 2026-07-30 | 383 |
| 2026-08-06 | 383 |
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## 🎓 Pragmatic AI Labs | Join 1M+ ML Engineers ### 🔥 Hot Course Offers: * 🤖 [Master GenAI Engineering](https://ds500.paiml.com/learn/course/0bbb5/) - Build Production AI Systems * 🦀 [Learn Professional Rust](https://ds500.paiml.com/learn/course/g6u1k/) - Industry-Grade Development * 📊 [AWS AI & Analytics](https://ds500.paiml.com/learn/course/31si1/) - Scale Your ML in Cloud * ⚡ [Production GenAI on AWS](https://ds500.paiml.com/learn/course/ehks1/) - Deploy at Enterprise Scale * 🛠️ [Rust DevOps Mastery](https://ds500.paiml.com/learn/course/ex8eu/) - Automate Everything ### 🚀 Level Up Your Career: * 💼 [Production ML Program](https://paiml.com) - Complete MLOps & Cloud Mastery * 🎯 [Start Learning Now](https://ds500.paiml.com) - Fast-Track Your ML Career * 🏢 Trusted by Fortune 500 Teams Learn end-to-end ML engineering from industry veterans at [PAIML.COM](https://paiml.com) [](https://github.com/noahgift/rust-mlops-template/actions/workflows/rust.yml) # rust-mlops-template A work in progress to build out solutions in Rust for MLOPs. This repo is more of a cookbook style. For a more gentle step by step guide to MLOps with Rust, please see my [lecture notes as a Rust MDBook here](https://nogibjj.github.io/rust-tutorial/).  Update, one of the more compelling projects to look at is [https://github.com/huggingface/candle](https://github.com/huggingface/candle) ## Take the Coursera Course! You can learn Rust from this Duke Coursera MLOps course:  [Take course here](https://www.coursera.org/learn/devops-dataops-mlops-duke). Direct link: [https://www.coursera.org/learn/devops-dataops-mlops-duke](https://www.coursera.org/learn/devops-dataops-mlops-duke) ## Demo Hitlist (Will Solve hopefully almost every day/weekly) * Do an [inline python example](https://github.com/fusion-engineering/inline-python) * Train a model in PyTorch with CPU: https://github.com/LaurentMazare/tch-rs * Train a model in PyTorch with GPU: https://github.com/LaurentMazare/tch-rs * Serve out ONNX with a Rust web framework like Actix * ONNX Command-Line Tool * Simple async network example: (network discovery or chat system) * Rust SQLite Example * Rust AWS Lambda * Simple Rust GUI * Rust Whisper Tool with [C++ Bindings](https://github.com/tazz4843/whisper-rs) * Fast Keyword Extraction (NLP) * Emit Random Mediterranean Meals via CLI * Web Assembly Rust ### Advanced Aspirational Demos * Building a database in Rust * Building a search engine in Rust * Building a web server in Rust * Building a batch processing systems in Rust * Build a command-line chat system * Build a locate clone * Build a load-testing tool ## Motivation One of the key goals of this project is to determine workflows that do not involve the #jcpennys (Jupyter, Conda, Pandas, Numpy, Sklearn) stack for #mlops. In particular I am not a fan of the conda installation tool (it is superfluous as [I demonstrate in the Python MLOps Template](https://github.com/nogibjj/mlops-template)) vs containerized workflows that use the Python Standard Library (Docker + pip + virtualenv) and this is a good excuse to find other solutions outside of that stack. For example: * Why not also find a more performant Data Frame library, faster speed, etc. * Why not have a compiler? * Why not have a simple packaging solution? * Why not have a very fast computational speed? * Why not be able to write both for the Linux Kernel and general purpose scripting? * Why not see if there is a better solution than Python (which is essentially two languages scientific python and regular Python)? * Python is one of the least green languages in
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:e9a5fa2cd213627e, topic:mlops, name:mlops, desc:mlops
matched fp:e9a5fa2cd213627e, topic:onnx
matched fp:e9a5fa2cd213627e, topic:gpu
matched fp:e9a5fa2cd213627e, topic:pytorch, topic:tensorflow