CV & Deep learning on IBM Red Hat OpenShift

IBM Developer New York
IBM Developer New York
Public group


150 Broadway 20th floor · New York, NY

How to find us

Join us on the 20th floor!

Location image of event venue


Are you interested how computers see? Want to easily build software that recognizes objects? Did that photograph contain a person on a motorbike? Finding that training a Computer Vision Deep Learning Model is hard or unreliable? If so then this workshop is for you!

Using IBM’s Model Asset Exchange (MAX) you will be able to create a microservice that lets you upload images where Deep Learning will return an annotated image with tag names, probabilities and categories.

In this meetup, you will learn...

By completing this workshop, you will learn how to deploy a deep learning microservice that uses IBM’s Model Asset Exchange MAX on your laptop and then deploy it to Red Hat OpenShift.

In addition, you will know how to use the OpenShift web console or the OpenShift Container platform command-line interface “oc” to:

- Create a new project
- Deploy a model-serving microservice from a public container image on Docker Hub
- Create a route that exposes the microservice to the public

Please bring a laptop follow along and Please sign up for IBM cloud via:

**Please bring your Meetup RSVP Confirmation & ID to check-in**


6:30-7pm: Registration, drinks, snacks, meet and greet
7pm-830pm: Presentation
8:30pm: Questions and Networking

About the Presenters :

Grant Steinfeld (@gsteinfeld) is the IBM Developer Advocate for Blockchain, Java, and NodeJS. Grant is an accomplished and innovative senior software architect and engineer with a reputation for delivering client-focused solutions. He is a problem solver and team mentor with the ability to work with and manage development teams. He is able to interface with senior management and product teams in order to translate business requirements and challenges into project plans and solutions.


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Learning Path series: An introduction to the Model Asset Exchange -Learn how to use state-of-the-art deep learning models in your applications or services

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