bacon VS tangram

Compare bacon vs tangram and see what are their differences.

bacon

Scientific Computing in Rust (by aftix)

tangram

Tangram makes it easy for programmers to train, deploy, and monitor machine learning models. (by tangramdotdev)
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bacon tangram
2 22
176 1,310
- -
3.4 9.6
2 days ago almost 2 years ago
Rust Rust
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

bacon

Posts with mentions or reviews of bacon. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-04.

tangram

Posts with mentions or reviews of tangram. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-01-11.
  • Writing the fastest GBDT libary in Rust
    6 projects | dev.to | 11 Jan 2022
    In this post, we will go over how we optimized our Gradient Boosted Decision Tree library. This is based on a talk that we gave at RustConf 2021: Writing the Fastest Gradient Boosted Decision Tree Library in Rust. The code is available on GitHub.
  • Any role that Rust could have in the Data world (Big Data, Data Science, Machine learning, etc.)?
    8 projects | /r/rust | 4 Dec 2021
  • Examples of Rust front-end web works
    5 projects | /r/rust | 7 Nov 2021
    We are using Rust for our web application and website at Tangram. You can view the source here: https://github.com/tangramdotdev/tangram/tree/main/crates/www. The website is at https://www.tangram.dev. We decided to write our own web framework because we needed server rendering and we wanted to use the builder pattern in creating components. Here is an example component for our Logo to get a sense of what this looks like: https://github.com/tangramdotdev/tangram/blob/main/crates/www/ui/logo.rs
  • Multi-language library support: Is it possible?
    4 projects | /r/rust | 6 Oct 2021
    Check out https://github.com/tangramdotdev/tangram.
  • Ask HN: Who is hiring? (October 2021)
    27 projects | news.ycombinator.com | 1 Oct 2021
    Tangram | Senior Rust Programmer | Remote | https://www.tangram.dev

    Tangram is an all in one machine learning framework designed for programmers. With Tangram, developers can train models and make predictions on the command line or with libraries for languages including Elixir, Go, JS, Python, Ruby, and Rust, and learn about their models and monitor them in production from a web application. To learn more about what the product does, watch the demo on the homepage at https://www.tangram.dev or check it out on GitHub at https://www.github.com/tangramdotdev/tangram.

    We are looking to grow our engineering team with senior Rust programmers. We are currently based in Boston, MA but are looking to build a remote team. At Tangram, you'll get to work on everything from our core machine learning algorithms to writing front-end code in Rust! We are looking for developers with experience in Rust and familiarity with or willingness to learn machine learning concepts. If this sounds exciting, email me (Isabella, cofounder) at [email protected].

  • Seed – A Rust front-end framework for creating fast and reliable web apps
    18 projects | news.ycombinator.com | 17 Sep 2021
    We chose to use Rust instead of TypeScript for the front end of https://github.com/tangramdotdev/tangram.

    This allows us to:

    * Share code with our server written in Rust.

  • How far along is the ML ecosystem with Rust?
    6 projects | /r/rust | 15 Sep 2021
    I'm working on machine learning in Rust at Tangram. We currently only provide an implementation of linear models and gradient boosted decision trees but will move into exposing training of deep models in the future. You can check out Tangram here: https://github.com/tangramdotdev/tangram. You may also be interested in checking out Linfa https://github.com/rust-ml/linfa. If you're interested in the future of machine learning in Rust, check out Luca Palmieri's blog post: https://www.lpalmieri.com/posts/2019-12-01-taking-ml-to-production-with-rust-a-25x-speedup/
  • Show HN: Tangram – Train, Deploy, and Monitor ML Models in Go/JS/Ruby/Rust/More
    4 projects | news.ycombinator.com | 18 Aug 2021
    Great idea! We definitely want to do this. We have an open issue to track it: https://github.com/tangramdotdev/tangram/issues/28.
    4 projects | news.ycombinator.com | 18 Aug 2021
    Hi HN! We are Isabella and David, and we're excited to share Tangram, our attempt to make it easy for programmers who are not machine learning experts to train, deploy, and monitor machine learning models. With Tangram, developers train a model from a CSV file on the command line, make predictions with libraries for Elixir, Go, JavaScript, Python, Ruby, and Rust, and learn about their models and monitor them in production with a convenient web app. Watch the video on the homepage: https://www.tangram.dev, or check it out on GitHub: https://github.com/tangramdotdev/tangram.

    Over the past few months we have been working closely with a handful of early users. A team at a small company had a TensorFlow model deployed as a Flask service consumed by their Elixir app. They replaced it with a Tangram model because they didn't want to maintain a server separate from their monolith. A team of front end engineers at a large company was looking for a way to to train and deploy models on their own, without the overhead of involving their data scientists, machine learning engineers, or backend engineers. They trained a model on their own and embedded it directly in their React front-end with the Tangram JavaScript library that makes predictions with WebAssembly.

    Tangram is written entirely in Rust, from the core machine learning algorithms, to the bindings for each language, to the front and back end of the web application. We have benefited from Rust's fast performance, strong typing, convenient tooling, and high quality libraries (serde, tokio, hyper, sqlx, and more).

    We hope to make Tangram a sustainable business with the "open core" business model. The CLI and language libraries are MIT licensed, while the web application is source available, free to use for testing, but requires a paid license to use in production.

    We would love to hear your feedback. Give it a try and let us know what you think!

    4 projects | news.ycombinator.com | 18 Aug 2021

What are some alternatives?

When comparing bacon and tangram you can also consider the following projects:

wtpsplit - Code for Where's the Point? Self-Supervised Multilingual Punctuation-Agnostic Sentence Segmentation

daisyui - 🌼 🌼 🌼 🌼 🌼  The most popular, free and open-source Tailwind CSS component library

tangram - WebGL map rendering engine for creative cartography

tangram - Tangram is an all-in-one automated machine learning framework. [Moved to: https://github.com/tangramdotdev/tangram]

openidconnect-rs - OpenID Connect Library for Rust

code - Source code for the book Rust in Action

rust-plus-golang - Rust + Go β€” Call Rust code from Go using FFI

fib - Performance Benchmark of top Github languages

sycamore - A library for creating reactive web apps in Rust and WebAssembly

neo4rs - Neo4j driver for rust

Boop-GTK - Port of @IvanMathy's Boop to GTK, a scriptable scratchpad for developers.

linfa - A Rust machine learning framework.