Fakhraee / Balakreshnan / Masanz Azure Machine Learning Engineering

Deploy, fine-tune, and optimize ML models using Microsoft Azure
1. Auflage 2023
ISBN: 978-1-80324-168-5
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 362 Seiten

No detailed description available for "Azure Machine Learning Engineering".

Autoren/Hrsg.

Fakhraee, Sina

Balakreshnan, Balamurugan

Masanz, Megan

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie

Inhaltsverzeichnis

Table of Contents - Introducing Azure Machine Learning
- Working with Data in AMLS
- Training Machine Learning Models in AMLS
- Tuning Your Models with AMLS
- Azure Automated Machine Learning
- Deploying ML Models for Real-Time Inferencing
- Deploying ML Models for Batch Scoring
- Responsible AI
- Productionizing Your Workload with MLOps
- Using Deep Learning in Azure Machine Learning
- Using Distributed Training in AMLS

Über Autor(innen)

Fakhraee Sina:
Sina Fakhraee, Ph.D., is currently working at Microsoft as an enterprise data scientist and senior cloud solution architect. He has helped customers to successfully migrate to Azure by providing best practices around data and AI architectural design and by helping them implement AI/ML solutions on Azure. Prior to working at Microsoft, Sina worked at Ford Motor Company as a product owner for Ford's AI/ML platform. Sina holds a Ph.D. degree in computer science and engineering from Wayne State University and prior to joining the industry, he taught various undergrad and grad computer science courses part time. Balakreshnan Balamurugan:
Balamurugan Balakreshnan is a principal cloud solution architect at Microsoft Data/AI Architect and Data Science. He has provided leadership on digital transformations with AI and cloud-based digital solutions. He has also provided leadership in terms of ML, the IoT, big data, and advanced analytical solutions.Masanz Megan:
Megan Masanz is a principal cloud solution architect at Microsoft focused on data, AI, and data science, passionately enabling organizations to address business challenges through the establishment of strategies and road maps for the planning, design, and deployment of Azure Cloud-based solutions. Megan is adept at paving the path to data science via computer science given her master's in computer science with a focus on data science.