DEPLOYING DEEP LEARNING MODEL AS A WEB APP

In the Practical Deep Learning for Coders, v3 Provided by Fast.ai several services are described for production such as:

We will deploy our deep learning model using Render, Render is a modern cloud provider that makes it trivial and instant to deploy your code in production. You can deploy anything on Render, from simple static sites and cron jobs to databases and Dockerized private services.

Render deploys your services directly from GitHub. All that’s needed is to push your code like you normally do — Render automatically updates your services and keeps them up and running at all times.

1>Fast CDN.

2>Automatic continuous deploys from git.

3>Custom domains with fully managed SSL.

4>Unlimited collaborators.

5>The http/2 and brotli compression.

1>Train you model
2>Sign up at render using invite code fastai-v3
3>Upload the trained model file created with learner.export to a cloud service like google drive or Dropbox. copy the download link for the file.

Create a new web service on render and use the repository you created earlier, grant render the permission of accessing the repository.On the deployment screen name, your service and docker is used as the container the URL will be created using the service name. the service name can be changed, but the URL once created can’t be edited further.
Click save web service. that’s it! your service will begin building and should be live in a few minutes at the URL displayed in your render dashboard. you can check its progress in the deploy logs.

Local testing
To run the app server locally, run this command in your terminal:
python app/server.py serve

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