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Storage and Analytics for Machine Learning
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Classroom Contents
Machine Learning Using Kubeflow and Kubernetes
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- 1 Intro
- 2 Machine Learning is Hard!
- 3 Storage and Analytics for Machine Learning
- 4 Amazon EKS: run Kubernetes in cloud
- 5 Getting started with Amazon EKS
- 6 Set up K8s for ML: Option 1
- 7 Scaling the cluster
- 8 Kubeflow Requirements
- 9 Kubeflow on Desktop
- 10 Kubeflow on Cloud
- 11 Jupyter Notebook
- 12 Kubeflow Fairing
- 13 Hyperparameter Tuning using Katib
- 14 Katib System Architecture
- 15 Pluggable Interface
- 16 Distributed Training using Horovod
- 17 Kubeflow Pipelines
- 18 Creating Kubeflow Pipeline Components
- 19 Consumer Loan Acceptance Scoring
- 20 Machine Learning pipeline for kubernetes on AWS
