Between ensuring that the right version of Python/Pip are installed on your system and that it doesn't conflict with other Python/Pip versions on your system AND that when you deploy your model to the cloud that the versions of the dependencies you've used in your projects are still compatible with the version on your cloud-based system, it's a wonder that we ever get any time to focus on building and training our neural networks.

Fortunately, there's a way to ensure that all of this is never a problem again - Containers!

With containers, we can create a clean, virtual environment to setup and train our neural networks in, and then deploy them at scale with the exact same environment. No more dependency hell!

- Learn why should you create a Containerized AI application.

- Learn how can you build your ML model to deploy in a containerized environment on IBM Cloud.

- Huzaifah Saleem, IBM Developer Advocate

https://www.linkedin.com/in/huzaifahsaleem/

https://www.linkedin.com/in/sidra-fatima/

- AI Developers, Data Scientists, Cloud Enthusiasts.

- Login/Sign up for your IBM Cloud account here: https://ibm.biz/Bdqt2s

- Create an IBM Cloud Kubernetes Cluster: https://cloud.ibm.com/kubernetes/overview

-Register for the event, event will be live on the same link: https://www.crowdcast.io/e/containerized-ml

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Deploy Containerized ML Models on IBM Cloud