課程資料
報名日期
全年招生
價錢
-
課程級別
學習模式
修業期
3 日
教學語言
英語
地點
-
34次瀏覽
課程簡介
This course teaches you how to use HPE Machine Learning Data Management and HPE Machine Learning Development Environment. Hands-on labs and activities will guide you through machine learning and deep learning fundamentals. You will learn about the architecture and ways to deploy HPE machine learning solutions. You will also explore HPE Machine Learning Data Management repos and pipelines.
Finally, you will understand:
- How to run deep learning experiments and train models using the HPE Machine Learning Development Environment.
- The HPE Machine Learning Development System, a solution that combines HPE Machine Learning Development Environment software and HPE infrastructure.
- How to position the HPE Machine Learning Development solutions based on customer needs and how to set up a proof of concept or demo environment.
Ideal candidate for this course
Typical candidates for this course are students needing to learn how to describe, position, recommend, and demonstrate the HPE Machine Learning Data Management and HPE Machine Learning Development solutions. This course will help candidates prepare for the exam: HPE2-T38 – HPE AI and Machine Learning.
課程內容
Understand Machine Learning and Deep Learning Fundamentals
- Machine learning technology evolution
- Machine learning and deep learning model training
- Consideration of issues data scientists confront during model training
- Standard tools and frameworks for deep learning pipelines such as PyTorch and TensorFlow
- Hyperparameter optimization (HPO)
- Distributed (multi-GPU) training
Describe HPE Machine Learning Solutions' Value Proposition
- HPE Machine Learning Data Management value proposition
- HPE Machine Learning Development Environment value proposition
- Common customer challenges in deep learning
- A high-level look at how HPE Machine Learning Data Management and HPE Machine Learning
- Development Environment address these challenges
- Where HPE machine learning solutions fits in the market
- A high-level look at HPE Machine Learning Data Management and HPE Machine Learning Environment capabilities
- Distinguishing features of HPE Machine Learning Development Systems
Using HPE Machine Learning Data Management Capabilities
- Repos and their data versioning and data lineage capabilities
- Pipelines and ways to use them
Using HPE Machine Learning Development Environment to Train Models
- HPE Machine Learning Development Environment software architecture
- Flexible options for software-only deployment on on-prem servers or in the cloud
- Intro to training a model on the HPE Machine Learning Development Environment
- Detailed AI and Machine Learning training concepts
- Using HPE Machine Learning Development Environment to run experiments, including experiments that feature distributed training and HPO
- Experiment concepts and the relationships between workloads, trials, and experiments
- Scheduling concepts
- Model registry
Qualifying Customers and Running a Demonstration
- Engaging and qualifying customers for an HPE Machine Learning Development Environment opportunity
- Engaging and qualifying customers for an HPE Machine Learning Development System opportunity
- Running a demonstration
