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Paperback. Condition: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Paperback or Softback. Condition: New. Managing Your Data Science Projects: Learn Salesmanship, Presentation, and Maintenance of Completed Models. Book.
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Language: English
Published by Apress, Incorporated, 2019
ISBN 10: 1484249062 ISBN 13: 9781484249062
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Taschenbuch. Condition: Neu. Managing Your Data Science Projects | Learn Salesmanship, Presentation, and Maintenance of Completed Models | Robert de Graaf | Taschenbuch | xii | Englisch | 2019 | Apress | EAN 9781484249062 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Published by Apress, Incorporated, 2019
ISBN 10: 1484249062 ISBN 13: 9781484249062
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -At first glance, the skills required to work in the data science field appear to be self-explanatory. Do not be fooled. Impactful data science demands an interdisciplinary knowledge of business philosophy, project management, salesmanship, presentation, and more. In Managing Your Data Science Projects, author Robert de Graaf explores important concepts that are frequently overlooked in much of the instructional literature that is available to data scientists new to the field. If your completed models are to be used and maintained most effectively, you must be able to present and sell them within your organization in a compelling way.The value of data science within an organization cannot be overstated. Thus, it is vital that strategies and communication between teams are dexterously managed. Three main ways that data science strategy is used in a company is to research its customers, assess risk analytics, and log operational measurements. These all require different managerial instincts, backgrounds, and experiences, and de Graaf cogently breaks down the unique reasons behind each. They must align seamlessly to eventually be adopted as dynamic models.Data science is a relatively new discipline, and as such, internal processes for it are not as well-developed within an operational business as others. With Managing Your Data Science Projects, you will learn how to create products that solve important problems for your customers and ensure that the initial success is sustained throughout the product's intended life. Your users will trust you and your models, and most importantly, you will be a more well-rounded and effectual data scientist throughout your career.Who This Book Is ForEarly-career data scientists, managers of data scientists, and those interested in entering the field of data science 156 pp. Englisch.
Language: English
Published by Apress, Incorporated, 2019
ISBN 10: 1484249062 ISBN 13: 9781484249062
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Seller: moluna, Greven, Germany
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Explores how you can use business strategies within your data science projects to best harness your technical skills Teaches you how to contextualize and present your technical data science with end users in mind.
Language: English
Published by Apress, Apress Jun 2019, 2019
ISBN 10: 1484249062 ISBN 13: 9781484249062
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -At first glance, the skills required to work in the data science field appear to be self-explanatory. Do not be fooled. Impactful data science demands an interdisciplinary knowledge of business philosophy, project management, salesmanship, presentation, and more. In Managing Your Data Science Projects, author Robert de Graaf explores important concepts that are frequently overlooked in much of the instructional literature that is available to data scientists new to the field. If your completed models are to be used and maintained most effectively, you must be able to present and sell them within your organization in a compelling way.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 156 pp. Englisch.
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - At first glance, the skills required to work in the data science field appear to be self-explanatory. Do not be fooled. Impactful data science demands an interdisciplinary knowledge of business philosophy, project management, salesmanship, presentation, and more. In Managing Your Data Science Projects, author Robert de Graaf explores important concepts that are frequently overlooked in much of the instructional literature that is available to data scientists new to the field. If your completed models are to be used and maintained most effectively, you must be able to present and sell them within your organization in a compelling way.The value of data science within an organization cannot be overstated. Thus, it is vital that strategies and communication between teams are dexterously managed. Three main ways that data science strategy is used in a company is to research its customers, assess risk analytics, and log operational measurements. These all require different managerial instincts, backgrounds, and experiences, and de Graaf cogently breaks down the unique reasons behind each. They must align seamlessly to eventually be adopted as dynamic models.Data science is a relatively new discipline, and as such, internal processes for it are not as well-developed within an operational business as others. With Managing Your Data Science Projects, you will learn how to create products that solve important problems for your customers and ensure that the initial success is sustained throughout the product's intended life. Your users will trust you and your models, and most importantly, you will be a more well-rounded and effectual data scientist throughout your career.Who This Book Is ForEarly-career data scientists, managers of data scientists, and those interested in entering the fieldof data science.