Keynote: Machine Learning using Kubeflow and Kubernetes

on YouTube ↗10m

" summary

Covers using Kubeflow on Kubernetes to run ML workflows, including Jupyter notebooks, TensorFlow training and inference, Katib for hyperparameter tuning, Argo pipelines for end-to-end automation, and TensorBoard for visualization. Describes Kubernetes-based single- and multi-node distributed training workflows and includes discussion of Horovod for distributed training.

AI-written summary · about

" chapters (5)

1. 0:00Start
2. 0:30End-to-End ML Workflow
3. 1:17Why Machine Learning on Kubernetes?
4. 2:54Machine Learning on K8s: Without KubeFlow
5. 4:08What is Kubeflow

" related talks

• 15mKeynote: Machine Learning on Kubernetes Made Easy With KubeflowMasoud Mirmomeni, Jimmy Guerrero · KubeCon + CloudNativeCon North America 2021
• 51mMachine Learning using Kubeflow and KubernetesArun Gupta · Devoxx Belgium 2019
• 46mKubeflow, TensorFlow on KubernetesIsrael Olalla · Commit Conf 2018
• 14mKubeflow: Where ML Meets KubernetesSuresh Peiris · KCD Sri Lanka 2023
• 30mKubeflow, Your ML Tools on KubernetesLaura Morillo, Iván Cañaveral · Commit Conf 2018
• 46mDeploying scalable Machine Learning models with KubernetesAlessandro Vozza · Future Tech 2019
• 22mKeynote: Kubeflow ML on KubernetesDavid Aronchick, Vishnu Kannan · KubeCon + CloudNativeCon Europe 2018
• 31mKubernetes for Machine Learning: Managing and Scaling AI WorkloadsDrishti Jain · KCD Mumbai 2023