The Easiest Way to Use Tensorflow Models in the Browser

Part 1: Create the Model

1.1 Importing the required packages

Part 2: Create the .air file

Now that the model itself has been created and saved, we can create the .air file that can be used to integrate the model into the browser workflow. The configuration of the .air file includes steps to determine data harvesting, data preprocessing, the analytic or model that is to be run on the data, result postprocessing and rendering, as well as how users can input feedback into the model. If you have any questions at this stage, I recommend consulting the aisquared documentation site to get more detail about how you can configure a model to run in the browser.

Part 3: Using the .air File

Now for the fun part — using your model in the browser!

This button that appeared onscreen when you ran the model will let you log feedback about the performance of your model.

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