Om kurset

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 clusters and provide real-life prediction analysis for specific use cases. The course consists of 30% lecture and 70% lab exercises.

Dette lærer du

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

Kursinnhold

Kurset dekker blant annet følgende temaer:

HJ7H2S (hpe.com)
Machine Learning Ops Overview
Creating an ML Ops tenant
External authentication
Project repository
Source control
Model registr
Training
Deployments
Data sources
App store
Notebooks HPE
Personas Overview • Platform administrator (siteadministrator)
Project administrator
Project member
Project Repository Setup • Initial access to HPE EzmeralContainer Platform
Setting up ML Ops environment and project repository
ML Ops clusters
Training Cluster Setup • Creating a training cluster
Training cluster configurations
Training cluster
Spark training
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 (Method 2)
Deployments clusters
Register and deploy the model
Inference • “Ready” deployment cluster
Doing inference
Walkthrough of scoring script
Local notebook to ML Ops training cluster
Lab 1: Initial Access to HPE Ezmeral Container
Platform • Task 1: Initial log-on to HPE Ezmeral ContainerPlatform
Management Console
Task 2: Lab system setup
Task 3: Initial log-on to controller
Lab 2: Setting Up ML Ops Environment and
Project Repository • Task 1: Set up the ML Ops environment
Task 2: Install and register app from App Catalog
Task 3: Setup the project repository
Lab 3: Create Training Clusters • Task 1: Create trainingcluster
Lab 4: Create Notebooks with Training Cluster • Task 1:Create notebook with training cluster
Lab 5: Training First Model • Task 1: Login to Jupyter hub •Task 2: Training the model
Lab 6: Register and Deploy the Model • Task 1: Register themodel • Task 2: Deploy the model
Lab 7: Inference • Task 1: Generate prediction requests
Lab 8: Local Notebook to ML Ops Training Cluster • Task 1:Making required file configurations
Task 2: Accessing training cluster through JupyterNotebook
Task 3: Training the model through local notebook
Lab 9: Spark Deployment • Task 1: Setup Spark deploymentenvironment
Task 2: Stopping cluster in AIML tenant
Task 3: Create Spark training cluster
Task 4: Create Spark notebook cluster
Task 5: Train the used car pricing model
Task 6: Register new model
Task 7: Deploy the model
Task 8: Inference

Forkunnskaper

• AI/ML application administrationexperience (Spark, Jupyter Notebook,Tensorflow, etc.)

• Experience in machine learning lifecycle(e.g. model training/development andmodel deployment)

• Bash/shell/python scriptin

Hvem passer kurset for?

System developers, big data application developers, business analysts, data scientists, data engineers.

Videre kurs

Not available. Please contact.

Kommende kurs

Kursdatoer

Ingen kommende kursdato er publisert ennå.

Kontakt oss for informasjon om neste gjennomføring.

SG Partner

Hvorfor velge SG Partner?

Vi gjør det enkelt å finne riktig kurs og riktig gjennomføring for deg og din virksomhet.

Offisielle kurs

Kursinnhold fra anerkjente teknologileverandører og fagmiljøer.

Erfarne instruktører

Praktisk og faglig undervisning med fokus på kompetanse du kan bruke.

Fleksibel gjennomføring

Velg mellom tilgjengelige virtuelle, fysiske og bedriftsinterne kurs.

Personlig rådgivning

Vi hjelper deg med å finne kurs og kompetanseløp som passer behovet ditt.

FAQ

Ofte stilte spørsmål

Hvor lenge varer kurset?

Kursets oppgitte varighet er 1.

Kan jeg ta en sertifisering?

Kurset kan være relevant som forberedelse til sertifisering. Se kursbeskrivelsen for informasjon om aktuell sertifisering og eksamen.

Hvilke forkunnskaper trenger jeg?

• AI/ML application administrationexperience (Spark, Jupyter Notebook,Tensorflow, etc.) • Experience in machine learning lifecycle(e.g. model training/development andmodel deployment) • Bash/shell/python scriptin

Hvem passer kurset for?

System developers, big data application developers, business analysts, data scientists, data engineers.

Kan kurset leveres som bedriftsinternt kurs?

Ja.

Hvor kan kurset leveres?

Kurset kan leveres over hele Norge, blant annet i Oslo, Kristiansand, Stavanger, Bergen, Trondheim og Tromsø.