October 28–31, 2019
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Hyperparameter tuning for TensorFlow using Katib and Kubeflow

1:30pm5:00pm Tuesday, October 29, 2019
Location: Grand Ballroom C/D

Who is this presentation for?

  • Data scientists, machine learning engineers, and DevOps engineers




Neelima Mukiri and Meenakshi Kaushik provide an introduction to model building and optimization for TensorFlow in any Kubernetes environment. Katib is a scalable and flexible hyperparameter tuning framework and is tightly integrated with Kubernetes. It can be easily run on a laptop or in a distributed production deployment, and Katib jobs and configuration can be easily ported to any Kubernetes cluster.

You’ll go hands-on and set up a single-node Kubernetes on a laptop using VirtualBox. Neelima and Meenakshi provide a sample dataset and an example configuration and Kubeflow Pipeline that demonstrates hyperparameter tuning automation. They’ll walk you through Katib and Kubeflow, discussing functionality and usage, and explain how to port the tutorial to an enterprise environment for production deployment.

Prerequisite knowledge

  • A basic understanding of machine learning (what a model is and how to evaluate and compare models) and Linux command line usage

Materials or downloads needed in advance

  • A laptop with VirtualBox installed (please make sure to have VirtualBox installed BEFORE arriving onsite)

What you'll learn

  • Gain hands-on experience creating and optimizing models using Katib on Kubeflow
  • Understand hyperparameter tuning and how to transfer the system to an on-premises or cloud environment for production use cases
Photo of Neelima Mukiri

Neelima Mukiri


Neelima Mukiri is a principal engineer in the Cloud Platform Solutions Group at Cisco, working on the architecture and development of Cisco’s Container Platform. Previously, she worked on the core virtualization layer at VMware and systems software in Samsung Electronics.

Photo of Meenakshi Kaushik

Meenakshi Kaushik


Meenakshi Kaushik is a product manager for Cisco Container Platform, an enterprise-grade Kubernetes offering that supports GPU and Kubeflow for hybrid AI and ML workloads. Meenakshi is interested in the AI and ML space and is excited to see how the technology can enhance human well-being and productivity.

Comments on this page are now closed.


Daniel Goncharov | Head of the lab
10/27/2019 7:30am PDT

Got it.
Thank you, Neelima.

Neelima Mukiri |
10/27/2019 6:34am PDT

Hi Daniel,

Sure, any Kubernetes cluster which supports dynamic volume provisioning(ability to create persistent volumes) is fine.

Daniel Goncharov | Head of the lab
10/27/2019 6:21am PDT

I just got an email, that states that I need to bring laptop with preinstalled:
Vagrant 2.2.5 or later
VirtualBox 6.0.14 or later

Is it ok if I install the required software on GCP cloud instance and use laptop only as thin client?

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