Predictive Analytics with Microsoft Azure Machine Learning: Build and Deploy Actionable Solutions in Minutes

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9781484204467: Predictive Analytics with Microsoft Azure Machine Learning: Build and Deploy Actionable Solutions in Minutes

Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis.

The purpose of this book is to provide a gentle and instructionally organized introduction to the field of data science and machine learning, with a focus on building and deploying predictive models.

The book also provides a thorough overview of the Microsoft Azure Machine Learning service using task oriented descriptions and concrete end-to-end examples, sufficient to ensure the reader can immediately begin using this important new service. It describes all aspects of the service from data ingress to applying machine learning and evaluating the resulting model, to deploying the resulting model as a machine learning web service. Finally, this book attempts to have minimal dependencies, so that you can fairly easily pick and choose chapters to read. When dependencies do exist, they are listed at the start and end of the chapter.

The simplicity of this new service from Microsoft will help to take Data Science and Machine Learning to a much broader audience than existing products in this space. Learn how you can quickly build and deploy sophisticated predictive models as machine learning web services with the new Azure Machine Learning service from Microsoft.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

About the Author :

Valentine Fontama is a Principal Data Scientist in the Data and Decision Sciences Group (DDSG) at Microsoft, where he leads external consulting engagements that deliver world-class Advanced Analytics solutions to Microsoft’s customers. Val has over 18 years of experience in data science and business. Following a PhD in Artificial Neural Networks, he applied data mining in the environmental science and credit industries. Before Microsoft, Val was a New Technology Consultant at Equifax in London where he pioneered the application of data mining to risk assessment and marketing in the consumer credit industry. He is currently an Affiliate Professor of Data Science at the University of Washington. In his prior role at Microsoft, Val was a Senior Product Marketing Manager responsible for big data and predictive analytics in cloud and enterprise marketing. In this role, he led product management for Microsoft Azure Machine Learning; HDInsight, the first Hadoop service from Microsoft; Parallel Data Warehouse, Microsoft’s first data warehouse appliance; and three releases of Fast Track Data Warehouse. He also played a key role in defining Microsoft’s strategy and positioning for in-memory computing.Val holds an M.B.A. in Strategic Management and Marketing from Wharton Business School, a Ph.D. in Neural Networks, a M.Sc. in Computing, and a B.Sc. in Mathematics and Electronics (with First Class Honors). He co-authored the book Introducing Microsoft Azure HDInsight, and has published 11 academic papers with 152 citations by over 227 authors.

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Valentine Fontama, Roger Barga, Wee-Hyong Tok
Edité par aPress, United States (2014)
ISBN 10 : 1484204468 ISBN 13 : 9781484204467
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Description du livre aPress, United States, 2014. Paperback. État : New. 1st ed.. Language: English . Brand New Book. Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis. The purpose of this book is to provide a gentle and instructionally organized introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book also provides a thorough overview of the Microsoft Azure Machine Learning service using task oriented descriptions and concrete end-to-end examples, sufficient to ensure the reader can immediately begin using this important new service. It describes all aspects of the service from data ingress to applying machine learning and evaluating the resulting model, to deploying the resulting model as a machine learning web service. Finally, this book attempts to have minimal dependencies, so that you can fairly easily pick and choose chapters to read. When dependencies do exist, they are listed at the start and end of the chapter.The simplicity of this new service from Microsoft will help to take Data Science and Machine Learning to a much broader audience than existing products in this space. Learn how you can quickly build and deploy sophisticated predictive models as machine learning web services with the new Azure Machine Learning service from Microsoft. N° de réf. du libraire CBL9781484204467

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Valentine Fontama, Roger Barga, Wee-Hyong Tok
Edité par aPress, United States (2014)
ISBN 10 : 1484204468 ISBN 13 : 9781484204467
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Description du livre aPress, United States, 2014. Paperback. État : New. 1st ed.. Language: English . Brand New Book. Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis. The purpose of this book is to provide a gentle and instructionally organized introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book also provides a thorough overview of the Microsoft Azure Machine Learning service using task oriented descriptions and concrete end-to-end examples, sufficient to ensure the reader can immediately begin using this important new service. It describes all aspects of the service from data ingress to applying machine learning and evaluating the resulting model, to deploying the resulting model as a machine learning web service. Finally, this book attempts to have minimal dependencies, so that you can fairly easily pick and choose chapters to read. When dependencies do exist, they are listed at the start and end of the chapter.The simplicity of this new service from Microsoft will help to take Data Science and Machine Learning to a much broader audience than existing products in this space. Learn how you can quickly build and deploy sophisticated predictive models as machine learning web services with the new Azure Machine Learning service from Microsoft. N° de réf. du libraire CBL9781484204467

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Roger Barga; Wee Hyong Tok; Valentine Fontama
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VALENTINE FONTAMA
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Description du livre État : New. Publisher/Verlag: Springer, Berlin | Build and Deploy Actionable Solutions in Minutes | Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis.The purpose of this book is to provide a gentle and instructionally organized introduction to the field of data science and machine learning, with a focus on building and deploying predictive models.The book also provides a thorough overview of the Microsoft Azure Machine Learning service using task oriented descriptions and concrete end-to-end examples, sufficient to ensure the reader can immediately begin using this important new service. It describes all aspects of the service from data ingress to applying machine learning and evaluating the resulting model, to deploying the resulting model as a machine learning web service. Finally, this book attempts to have minimal dependencies, so that you can fairly easily pick and choose chapters to read. When dependencies do exist, they are listed at the start and end of the chapter.The simplicity of this new service from Microsoft will help to take Data Science and Machine Learning to a much broader audience than existing products in this space. Learn how you can quickly build and deploy sophisticated predictive models as machine learning web services with the new Azure Machine Learning service from Microsoft. | Part 1: Introducing Data Science and Microsoft Azure machine Learning1. Introduction to Data Science2. Introducing Microsoft Azure Machine Learning3. Integration with RPart 2: Statistical and Machine Learning Algorithms4. Introduction to Statistical and Machine Learning AlgorithmsPart 3: Practical applications5. Customer propensity models6. Building churn models7. Customer segmentation models8. Predictive Maintenance | Format: Paperback | Language/Sprache: english | 288 gr | 240x151x10 mm | 188 pp. N° de réf. du libraire K9781484204467

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Barga, Roger, Tok, Wee Hyong, Valentine
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Valentine Fontama
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Description du livre APRESS L.P. Dez 2014, 2014. Taschenbuch. État : Neu. Neuware - Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis. 166 pp. Englisch. N° de réf. du libraire 9781484204467

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Valentine Fontama
Edité par APRESS L.P. Dez 2014 (2014)
ISBN 10 : 1484204468 ISBN 13 : 9781484204467
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Description du livre APRESS L.P. Dez 2014, 2014. Taschenbuch. État : Neu. Neuware - Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis. 166 pp. Englisch. N° de réf. du libraire 9781484204467

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