Körner / Korner / Waaijer Mastering Azure Machine Learning

Perform large-scale end-to-end advanced machine learning in the cloud with Microsoft Azure Machine Learning
1. Auflage 2020
ISBN: 978-1-78980-152-1
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 436 Seiten

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

Autoren/Hrsg.

Körner, Christoph

Christoph Korner, Korner

Waaijer, Kaijisse

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

Table of Contents - Building an End-to-end Machine Learning Pipeline
- Choosing a Machine Learning Service in Azure
- Data Experimentation and Visualization using Azure
- ETL, Data Preparation and Feature Extraction
- Advanced Feature Extraction with NLP
- Building ML Models using Azure Machine Learning
- Training Deep Neural Networks on Azure
- Hyperparameter Tuning and Automated Machine Learning
- Distributed Machine Learning on Azure ML Clusters
- Building a Recommendation Engine in Azure
- Deploying and Operating Machine Learning Models
- MLOps

- What's next?

Über Autor(innen)

Körner Christoph:

Christoph Körner previously worked as a cloud solution architect for Microsoft, specializing in Azure-based big data and machine learning solutions, where he was responsible for designing end-to-end machine learning and data science platforms. He currently works for a large cloud provider on highly scalable distributed in-memory database services. Christoph has authored four books: Deep Learning in the Browser for Bleeding Edge Press, as well as Mastering Azure Machine Learning (first edition), Learning Responsive Data Visualization, and Data Visualization with D3 and AngularJS for Packt Publishing.Waaijer Kaijisse:

Kaijisse Waaijer is an experienced technologist specializing in data platforms, machine learning, and the Internet of Things. Kaijisse currently works for Microsoft EMEA as a data platform consultant specializing in data science, machine learning, and big data. She works constantly with customers across multiple industries as their trusted tech advisor, helping them optimize their organizational data to create better outcomes and business insights that drive value using Microsoft technologies. Her true passion lies within the trading systems automation and applying deep learning and neural networks to achieve advanced levels of prediction and automation.