Create a Deep Learning API with Python and FastAPI

Published: 14 November 2022
on channel: Dataquest

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We'll build a translation API using deep learning. Using FastAPI, we'll create a web server that exposes a /translate route and a /results route. Clients will post their translation request to the /translate route, and get the translation results from /results. The server will use a sqlite database to store the translations. On the backend, we'll use async and a pretrained deep learning language model to run the translation job.

By the end, we'll have a web server that can run translation jobs quickly. This server can easily be extended to translate more languages, or add more options.

Here's a link to the full code - https://github.com/dataquestio/projec... .

Chapters

0:00 Introduction
3:48 Build a database model
8:01 The index route
11:35 The translate route
17:08 Translating with deep learning
27:31 Showing results
31:01 Wrap-up and improvements

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