[HN Gopher] Show HN: Tangram - Train a model from a CSV file on ...
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       Show HN: Tangram - Train a model from a CSV file on the command
       line
        
       Author : nitsky
       Score  : 17 points
       Date   : 2021-08-18 14:03 UTC (1 days ago)
        
 (HTM) web link (www.tangram.dev)
 (TXT) w3m dump (www.tangram.dev)
        
       | ujeezy wrote:
       | I love the simplicity - this tickles my brain in the same way
       | that Firebase did when I first saw it :) Well done! Looking
       | forward to playing with it.
        
         | nitsky wrote:
         | Cool! Let us know how it works for you, and open an issue on
         | GitHub if you run into any trouble!
        
       | nitsky wrote:
       | Hi HN! We are Isabella and David, and we're excited to share
       | Tangram, our attempt to make ML easy for programmers who are not
       | experts. With Tangram, you train a model from a CSV file on the
       | command line, use your model from one of many languages (so far
       | we have libraries for Elixir, Go, JavaScript, Python, Ruby, and
       | Rust), and learn about your models and monitor them in production
       | from a web app. There's a video on our homepage
       | (https://www.tangram.dev) and we're on GitHub at
       | https://github.com/tangramdotdev/tangram.
       | 
       | Over the past few months we have been working 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!
        
       | drewcoo wrote:
       | name collision: https://mathigon.org/tangram
        
       | emhagman wrote:
       | We use this at Drafted (https://www.drafted.us). It's been huge
       | in helping us quickly train and deploy our classification models.
       | The bindings into Elixir and Go helped us keep everything in our
       | code base. We got to get rid of our Python TensorFlow app which
       | we had to deploy multiple instances of for acceptable
       | performance. All gone with Tangram. One model, any language. I
       | would definitely give this a try if you can.
        
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       (page generated 2021-08-19 23:01 UTC)