Offered By: IBM
Deploy a Computer Vision App in a Serverless Environment
Learn how to make your object detection application available to the world by deploying to a serverless environment. Focus on building your app instead of buying, installing or configuring servers.
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Guided Project
Containers
429 EnrolledAt a Glance
Learn how to make your object detection application available to the world by deploying to a serverless environment. Focus on building your app instead of buying, installing or configuring servers.
About
Serverless has quickly become one of the hottest topics among developers, but what is it exactly? Serverless is a cloud-native deployment model that allows developers to build and run applications without having to manage servers and other infrastructure. Once deployed, serverless apps respond to demand and automatically scale up and down as needed. Serverless offerings from public cloud providers are usually metered based on demand. As a result, when a serverless function is sitting idle, it doesn’t cost anything.
A Look at the Project Ahead
-Â Describe how you can build a python appplication in a Docker image
-Â Understand basic Docker commands to run Docker containers
-Â Deploy your object detection web app to IBM Code Engine
What You’ll Need Â
Everything else is provided to you via the IBM Skills Network Labs environment, where you will have access to the Cloud IDE and a Docker installation that we offer as part of the IBM Skills Network Labs environment.Â
This platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer or Safari.
Your Instructors
Estimated Effort
45 Minutes
Level
Beginner
Skills You Will Learn
Serverless, DevOps, Computer Vision, PyTorch
Language
English
Instructors
Joseph Santarcangelo
Senior Data Scientist at IBM
Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.
Read moreRichard Ye
Skills Network Data Scientist
A student of statistics interested in Machine Learning, Deep Learning (NLP specifically) and software development.
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