Deploying a Pytorch Computer Vision Model API to Heroku

von
Coursera Project Network
In diesem angeleitetes Projekt werden Sie:

Build a PyTorch computer vision model REST API with Flask.

Deploy PyTorch computer vision model REST API to Heroku.

Clock2 hours
IntermediateMittel
CloudKein Download erforderlich
VideoVideo auf geteiltem Bildschirm
Comment DotsEnglisch
LaptopNur Desktop

Welcome to the “Deploying a Pytorch Computer Vision Model API to Heroku” guided project. Computer vision is one of the prominent fields of AI with numerous applications in the real world including self-driving cars, image recognition, and object tracking, among others. The ability to make models available for real-world use is an essential skill anyone interested in AI engineering should have especially for computer vision and this is why this project exists. In this project, we will deploy a Flask REST API using one of Pytorch's pre-trained computer vision image classification models. This API will be able to receive an image, inference the pre-trained model, and return its predicted classification. This project is an intermediate python project for anyone interested in learning about how to productionize Pytorch computer vision models in the real world via a REST API on Heroku. It requires preliminary knowledge on how to build and train PyTorch models (as we will not be building or training models), how to utilize Git and a fundamental understanding of REST APIs. Learners would also need a Heroku account and some familiarity with the Python Flask module and the Postman API Platform. At the end of this project, learners will have a publicly available API they can use to demonstrate their knowledge in deploying computer vision models.

Kompetenzen, die Sie erwerben werden

  • Machine Learning
  • Python Programming
  • pytorch
  • Machine Learning Deployment
  • Computer Vision

Schritt für Schritt lernen

In einem Video, das auf einer Hälfte Ihres Arbeitsbereichs abgespielt wird, führt Sie Ihr Dozent durch diese Schritte:

  1. Import all the necessary libraries.

  2. Build a PyTorch computer vision model REST API with Flask.

  3. Build a simple flask web server.

  4. Test out PyTorch computer vision model REST API localhost end point.

  5. Deploy PyTorch computer vision model REST API to Heroku

  6. Test out PyTorch computer vision model REST API Heroku end point.

  7. Capstone Practice

Ablauf angeleiteter Projekte

Ihr Arbeitsbereich ist ein Cloud-Desktop direkt in Ihrem Browser, kein Download erforderlich

Ihr Dozent leitet Sie in einem Video mit geteiltem Bildschirm Schritt für Schritt an.

Häufig gestellte Fragen

Häufig gestellte Fragen

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