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Da: Lakeside Books, Benton Harbor, MI, U.S.A.
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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Prima edizione
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 44,75
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Da: Revaluation Books, Exeter, Regno Unito
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Aggiungi al carrelloPaperback. Condizione: Brand New. 294 pages. 9.25x6.10x0.62 inches. In Stock.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 53,00
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Da: Kennys Bookstore, Olney, MD, U.S.A.
Condizione: New. 2023. 1st ed. paperback. . . . . . Books ship from the US and Ireland.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 52,22
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Da: preigu, Osnabrück, Germania
EUR 50,25
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Introduction to Datafication | Implement Datafication Using AI and ML Algorithms | Shivakumar R. Goniwada | Taschenbuch | xix | Englisch | 2023 | Apress | EAN 9781484294956 | 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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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -What You Will LearnAPress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 296 pp. Englisch.
Da: Buchpark, Trebbin, Germania
EUR 27,91
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Aggiungi al carrelloCondizione: Hervorragend. Zustand: Hervorragend | Seiten: 296 | Sprache: Englisch | Produktart: Bücher | Beginning-Intermediate user level.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 46,56
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 58,84
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents the process and framework you need to transform aspects of our world into data that can be collected, analyzed, and used to make decisions. You will understand the technologies used to gather and process data from many sources, and you will learn how to analyze data with AI and ML models.Datafication is becoming increasingly prevalent in many areas of our lives, from business to education and healthcare. It has the potential to improve decision-making by providing insights into patterns, trends, and correlation between seemingly unconnected pieces of data. This book explains the evolution, principles, and patterns of datafication used in our day-to-day activities. It covers how to collect data from a variety of sources, using technologies such as edge, streaming techniques, REST, and frameworks, as well as data cleansing and data lineage. A data analysis framework is provided to guide you in designing and developing AI and ML projects, including the details of sentiment and behavioral analytics.Introduction to Datafication teaches you how to engineer AI and ML projects by using various methodologies, covers the security mechanisms to be applied for datafication, and shows you how to govern the datafication process with a well-defined governance framework.What You Will LearnUnderstand the principles and patterns to be adopted for dataficationGain techniques for sourcing and mining data, and for sharing data with a data pipelineLeverage the AI and ML algorithms most suitable for dataficationUnderstand the data analysis framework used in every AI and ML projectMaster the details of sentiment and behavioral analytics through practical examplesUtilize development methodologies for datafication engineering and the related security and governance framework Who This Book Is ForStudents, data scientists, data analysts, and AI and ML engineers 296 pp. Englisch.
Da: CitiRetail, Stevenage, Regno Unito
Prima edizione Print on Demand
EUR 52,87
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. This book presents the process and framework you need to transform aspects of our world into data that can be collected, analyzed, and used to make decisions. You will understand the technologies used to gather and process data from many sources, and you will learn how to analyze data with AI and ML models.Datafication is becoming increasingly prevalent in many areas of our lives, from business to education and healthcare. It has the potential to improve decision-making by providing insights into patterns, trends, and correlation between seemingly unconnected pieces of data. This book explains the evolution, principles, and patterns of datafication used in our day-to-day activities. It covers how to collect data from a variety of sources, using technologies such as edge, streaming techniques, REST, and frameworks, as well as data cleansing and data lineage. A data analysis framework is provided to guide you in designing and developing AI and ML projects, including the details of sentiment and behavioral analytics.Introduction to Datafication teaches you how to engineer AI and ML projects by using various methodologies, covers the security mechanisms to be applied for datafication, and shows you how to govern the datafication process with a well-defined governance framework.What You Will LearnUnderstand the principles and patterns to be adopted for dataficationGain techniques for sourcing and mining data, and for sharing data with a data pipelineLeverage the AI and ML algorithms most suitable for dataficationUnderstand the data analysis framework used in every AI and ML projectMaster the details of sentiment and behavioral analytics through practical examplesUtilize development methodologies for datafication engineering and the related security and governance frameworkWho This Book Is ForStudents, data scientists, data analysts, and AI and ML engineers Beginning-Intermediate user level This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Da: moluna, Greven, Germania
EUR 48,37
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book presents the process and framework you need to transform aspects of our world into data that can be collected, analyzed, and used to make decisions. You will understand the technologies used to gather and process data from many sources, and you wi.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 59,97
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents the process and framework you need to transform aspects of our world into data that can be collected, analyzed, and used to make decisions. You will understand the technologies used to gather and process data from many sources, and you will learn how to analyze data with AI and ML models.Datafication is becoming increasingly prevalent in many areas of our lives, from business to education and healthcare. It has the potential to improve decision-making by providing insights into patterns, trends, and correlation between seemingly unconnected pieces of data. This book explains the evolution, principles, and patterns of datafication used in our day-to-day activities. It covers how to collect data from a variety of sources, using technologies such as edge, streaming techniques, REST, and frameworks, as well as data cleansing and data lineage. A data analysis framework is provided to guide you in designing and developing AI and ML projects, including the details of sentiment and behavioral analytics.Introduction to Datafication teaches you how to engineer AI and ML projects by using various methodologies, covers the security mechanisms to be applied for datafication, and shows you how to govern the datafication process with a well-defined governance framework.What You Will LearnUnderstand the principles and patterns to be adopted for dataficationGain techniques for sourcing and mining data, and for sharing data with a data pipelineLeverage the AI and ML algorithms most suitable for dataficationUnderstand the data analysis framework used in every AI and ML projectMaster the details of sentiment and behavioral analytics through practical examplesUtilize development methodologies for datafication engineering and the related security and governance framework Who This Book Is ForStudents, data scientists, data analysts, and AI and ML engineers.