Create a Deep Learning API with Python and FastAPI

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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.

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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Комментарии
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How would be with my API need as parameter an Image? Love the video

lucaslessa
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Hi Vikas, great job. Just wanted to understand what is the need to create DB and store translation/ID etc and all stuff. Cant we do direct live translation without creating sqlite DB or any DB for that matter?

madhuful
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Amazing. Bu i didnt undestand abou the model. Did you download it, our the hugging face just connected and translate?

romariogomes
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You are good, sir! Very good! Thank you for sharing the knowledge. Regards from Nairobi, Kenya

vectorautomationsystems
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Hey vik loving this videos...gonna sigh up for dataquest

nickpinto