Predictive Analytics with Microsoft Azure Machine Learning 2nd Edition
Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Programming, Software Development, General Computing
| Author: | Valentine Fontama, Roger Barga, Wee Hyong Tok | ISBN: | 9781484212004 |
| Publisher: | Apress | Publication: | August 26, 2015 |
| Imprint: | Apress | Language: | English |
| Author: | Valentine Fontama, Roger Barga, Wee Hyong Tok |
| ISBN: | 9781484212004 |
| Publisher: | Apress |
| Publication: | August 26, 2015 |
| Imprint: | Apress |
| Language: | English |
Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book provides a thorough overview of the Microsoft Azure Machine Learning service released for general availability on February 18th, 2015 with practical guidance for building recommenders, propensity models, and churn and predictive maintenance models.
The authors use task oriented descriptions and concrete end-to-end examples to ensure that the reader can immediately begin using this new service. The book describes all aspects of the service from data ingress to applying machine learning, evaluating the models, and deploying them as web services.
Learn how you can quickly build and deploy sophisticated predictive models with the new Azure Machine Learning from Microsoft.
What’s New in the Second Edition?
Five new chapters have been added with practical detailed coverage of:
- Python Integration – a new feature announced February 2015
- Data preparation and feature selection
- Data visualization with Power BI
- Recommendation engines
- Selling your models on Azure Marketplace
Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book provides a thorough overview of the Microsoft Azure Machine Learning service released for general availability on February 18th, 2015 with practical guidance for building recommenders, propensity models, and churn and predictive maintenance models.
The authors use task oriented descriptions and concrete end-to-end examples to ensure that the reader can immediately begin using this new service. The book describes all aspects of the service from data ingress to applying machine learning, evaluating the models, and deploying them as web services.
Learn how you can quickly build and deploy sophisticated predictive models with the new Azure Machine Learning from Microsoft.
What’s New in the Second Edition?
Five new chapters have been added with practical detailed coverage of:
- Python Integration – a new feature announced February 2015
- Data preparation and feature selection
- Data visualization with Power BI
- Recommendation engines
- Selling your models on Azure Marketplace
