Course Overview
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.
Moyens d'évaluation :
- Quiz pré-formation de vérification des connaissances (si applicable)
- Évaluations formatives pendant la formation, à travers les travaux pratiques réalisés sur les labs à l’issue de chaque module, QCM, mises en situation…
- Complétion par chaque participant d’un questionnaire et/ou questionnaire de positionnement en amont et à l’issue de la formation pour validation de l’acquisition des compétences
Who should attend
System Developers, Big Data Application Developers, Business Analysts, Data Scientists, Data Engineers, Support Engineers, Platform/Project Administrators
Prerequisites
- 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
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
Course Content
- Machine Learning Ops Overview
- Personas Overview
- Project Repository Setup
- Training Cluster Setup
- Ezmeral Container Platform[/h5]
- Notebook Setup
- Model Registry and Deployment
- Inference
Moyens Pédagogiques :