Getting Started with Project Oxford Machine Learning APIs and Deployment on Azure

Project Oxford is cool. I am out at a lot of hackathons where I see students creating some amazing applications. While at the hackathons I see students struggling to get started with Project Oxford in their language of choice. Project Oxford is so powerful that I hate to see students struggle getting started so I created a series of videos and sample projects to get them started quickly. But Project Oxford is not only for hackathons and students. Project Oxford has tons of real world applications such as image and video processing, OCR, and text to speech.

By the end of the videos you will have a full working sample and learn a few tricks like using the Kudu Dashboard along the way.

  1. Introduction to Project Oxford Machine Learning API’s
  2. How to set up your local Python environment for development and testing
  3. Configuring GitHub Continuous Deployment on Azure with Project Oxford Application

Sample projects

The sample project that used in the series is located at https://github.com/jsturtevant/happy-image-tester-django. If you prefer Node.js I have a made a similar project located at https://github.com/jsturtevant/happy-image-tester-nodejs.

Project Oxford API’s

You can find API wrappers for many of the languages:

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