Create a Deep Learning API with Python and FastAPI

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/project-walkthroughs/tree/master/dl_api . 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 ----------------------------- Join 1M+ Dataquest learners today! Master data skills and change your life. Sign up for free: https://bit.ly/3O8MDef