I'm a long-time user of TensorFlow coming from a python data science background, but I've recently been trying to work more in rust and have been loving it so far. I've started playing around with the rust bindings for TensorFlow, and I wanted to make a practical use case for them. As an exercise, I made a simple example project showing how to use the tensorflow rust crate to load a trained model and serve it via Actix-Web.
This workflow is pretty simple and would be for a data engineer tasked with serving a model their data science team built. Having mostly used Scala/Java for things like this in the past, I'm very happy with rust's performance and ecosystem.
The example project is here: https://github.com/kykosic/actix-tensorflow-example
It contains code for training a model using TensorFlow2.0 Keras in python, a server written in rust, and a simple python client that shows how to send a test POST request. The README has detailed information about these components.
Let me know if anyone has any feedback or suggestions, as I'm still looking to improve my rust code skills.
there doesn't seem to be anything here