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Hyper Parameters
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Classroom Contents
Scaling Machine Learning Pipelines in Cloud
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- 1 Intro
- 2 About Salman
- 3 Giveaway
- 4 Agenda
- 5 Who is this talk for
- 6 Training Models
- 7 Docker
- 8 Where can we run Kubernetes
- 9 Benefits of Kubernetes
- 10 Scaling Pipelines with Kubernetes
- 11 Introducing Kubernetes
- 12 Data Science Machine Learning Engineers
- 13 Kubernetes tools
- 14 Operators
- 15 Fashion mnist
- 16 Neural Network
- 17 Hyper Parameters
- 18 Auto ML
- 19 Serving
- 20 kubeflow
- 21 Why Kubernetes
- 22 Data Science and Machine Learning
- 23 QFlow Pipeline
- 24 MiniCube
- 25 Python Pipeline SDK
- 26 GPU Pipeline
- 27 GPU Worker
- 28 Experimenting
- 29 Running the pipeline
- 30 Kale
- 31 Notebook
- 32 Kubernetes Extension
- 33 Adding Labels
- 34 Creating a Pipeline
- 35 Scaling Pipelines
- 36 Kubernetes Autoscaling
- 37 Considerations
- 38 Platform Management
- 39 OpenAI
- 40 Summary
- 41 References
- 42 Thanks
- 43 Outro
