Szkolenia HPE

Cel szkolenia szkolenie zdalne - dlearning

kod: HJ7H2S | wersja: 5.x

This course is for developers who create and run machine learning applications on HPE Ezmeral Container Platform 5.3. The course teaches how to deploy Kubernetes clusters and provide real-life prediction analysis for specific use cases.

Course objectives

During this course, you will learn how to:

  • Set up the project repository
  • Create a training cluster
  • Create a Jupyter notebook and attach it to a training cluster
  • Run through an example of a typical machine learning workflow
  • Operationalize your model
  • Make a prediction (inference)
  • Obtain in-depth knowledge of HPE Ezmeral Container Platform 5.3 ML Ops
  • Apply best practices to help accelerate the development of user-based prediction analysis

Audience

  • System Developers,
  • Big Data Application Developers,
  • Business Analysts,
  • Data Scientists,
  • Data Engineers,
  • Support Engineers,
  • Platform/Project Administrators

Plan szkolenia Rozwiń listę

  • Machine Learning Ops Overview
    • Creating an ML Ops tenant
    • External authentication
    • Project repository
    • Source control
    • Model registr
    • Training
    • Deployments
    • Data sources
    • Notebooks HPE
  • Personas Overview
    • Platform administrator (site administrator)
    • Project administrator
    • Project member
  • Project Repository Setup
    • Initial access to HPE Ezmeral Container Platform
    • Setting up ML Ops environment and project repository
    • ML Ops clusters
  • Training Cluster Setup
    • Creating a training cluster
    • Training cluster configurations
    • Training cluster
    • Accessing Python training cluster outside of HPE
  • Ezmeral Container Platform
    • General notes on training clusters
  • Notebook Setup
    • Creating a notebook cluster
    • Notebook cluster configuration
    • More details on notebooks on ML Ops
    • Create notebook with training cluster
    • Review
    • Training first model
  • Model Registry and Deployment
    • Model registry
    • Model registry configurations
    • More details on model registry
    • Deployments (Method 1)
    • Deployments clusters
    • Register and deploy the model
  • Inference
    • “Ready” deployment cluster
    • Doing inference
    • Walkthrough of scoring script
    • Local notebook to ML Ops training cluster
Pobierz konspekt szkolenia w formacie PDF

Dodatkowe informacje

Wymagania wstępne
  • AI/ML application administration experience (Spark, Jupyter Notebook, Tensorflow, etc.)
  • Experience in machine learning lifecycle (e.g., model training/development and model deployment)
  • Bash/shell/python scripting
Poziom trudności
Czas trwania 1 dzień
Certyfikat

The participants will obtain certificates signed by HPE (course completion).
Prowadzący

Authorized HPE Trainer.

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