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Microsoft Azure Machine Learning
Microsoft Azure Machine Learning
Building and deploying the right solution
This book introduces data science and machine learning with a focus on building and deploying predictive models and provides practical examples. It also provides a complete overview of the Microsoft Azure Machine Learning service that was released in early 2015, along with a practical guide to building referral and propensity models and exit and predictive management models. To help readers understand their work using task-oriented explanations and concrete and complete examples. This book is a new machine learning service that covers everything from data entry to applying machine learning, evaluating models, and deploying as Web services. This is an easy to understand way to learn how to build and deploy complex forecasting models with Microsofts Azot Machine Running.
What changed in the second edition? With six new chapters, you will find practical and detailed information on the following
Kotana Analytics Suite - Python integration - Data preparation and feature selection - Visualizing Data with Power BI
- Structured Introduction of Best Practices
- Introduction of the new Microsoft Azure Machine Learning Services and Explanation of how to efficiently build and distribute forecasting models
- General forecasts such as propensity modeling, departure analysis, product recommendation and visualization with Power BI Practical techniques for solving analytical problems
A practical way to sell your own predictive models to the bazaar marketplace
Building and deploying the right solution
This book introduces data science and machine learning with a focus on building and deploying predictive models and provides practical examples. It also provides a complete overview of the Microsoft Azure Machine Learning service that was released in early 2015, along with a practical guide to building referral and propensity models and exit and predictive management models. To help readers understand their work using task-oriented explanations and concrete and complete examples. This book is a new machine learning service that covers everything from data entry to applying machine learning, evaluating models, and deploying as Web services. This is an easy to understand way to learn how to build and deploy complex forecasting models with Microsofts Azot Machine Running.
What changed in the second edition? With six new chapters, you will find practical and detailed information on the following
Kotana Analytics Suite - Python integration - Data preparation and feature selection - Visualizing Data with Power BI
- Structured Introduction of Best Practices
- Introduction of the new Microsoft Azure Machine Learning Services and Explanation of how to efficiently build and distribute forecasting models
- General forecasts such as propensity modeling, departure analysis, product recommendation and visualization with Power BI Practical techniques for solving analytical problems
A practical way to sell your own predictive models to the bazaar marketplace
Paperback
Published May 26, 2016
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