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Deploy a computer vision model as an API

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Emmanuel Acheampong

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What you'll learn

Build a python flask API

Build a python flask API for an already trained Pytorch computer vision model.

Deploy flask API to the web

Deploy flask API to a Heroku account where it can be accessed publicly.

Test API with Postman/Curl

Send API calls to Heroku website through curl commands on the command shell and Postman.

Why this topic matters

Deploying models allows external users to be able to access trained ML models. This is where the value of AI is... people can only interact with AI after it is has been deployed. Deploying an API makes it easy for developers and for other web or mobile applications to be able to use trained models.

You'll learn from

Emmanuel Acheampong

Co-Founder/Head of AI @ roboMUA, Notre Dame masters, Morgan Stanley, Microsoft, AI projects course instructor Coursera

Emmanuel Acheampong - co-founder and CEO of roboMUA, leads an AI solutions company specializing in comprehensive skin recognition and analysis. A Notre Dame ESTEEM program graduate, he explored AI's intersection with directed energy weapons in his Master's thesis. Under his leadership, roboMUA's custom AI algorithms earned them the 2023 Technology of the Year award at the Smart Retail Tech Conference. A passionate educator, Emmanuel has taught AI courses to over 4000 students on Coursera and spoken at major AI conferences like Ai4, AI DevWorld, and AI Retail Africa.

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