ISBN: 9781484239506 - practical java machine learning: projects with google cloud platform and amazon web services (27 risultati)

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Paperback. Condizione: New. Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. Practical Java Machine Learning helps you understand the importance of data and how to organize it for use within your ML project. You will be introduced to tools which can help you identify and manage your data including JSON, visualization, NoSQL databases, and cloud platforms including Google Cloud Platform and Amazon Web Services.Practical Java Machine Learning includes multiple projects, with particular focus on the Android mobile platform and features such as sensors, camera, and connectivity, each of which produce data that can power unique machine learning solutions. You will learn to build a variety of applications that demonstrate the capabilities of the Google Cloud Platform machine learning API, including data visualizationfor Java; document classification using the Weka ML environment; audio file classification for Android using ML with spectrogram voice data; and machine learning using device sensor data.After reading this book, you will come away with case study examples and projects that you can take away as templates for re-use and exploration for your own machine learning programming projects with Java.What You Will LearnIdentify, organize, and architect the data required for ML projectsDeploy ML solutions in conjunction with cloud providers such as Google and AmazonDetermine which algorithm is the most appropriate for a specific ML problemImplement Java ML solutions on Android mobile devicesCreate Java ML solutions to work with sensor dataBuild Java streaming based solutionsWho This Book Is ForExperienced Java developers who have not implemented machine learning techniques before.…

Paperback. Condizione: New. Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. Practical Java Machine Learning helps you understand the importance of data and how to organize it for use within your ML project. You will be introduced to tools which can help you identify and manage your data including JSON, visualization, NoSQL databases, and cloud platforms including Google Cloud Platform and Amazon Web Services.Practical Java Machine Learning includes multiple projects, with particular focus on the Android mobile platform and features such as sensors, camera, and connectivity, each of which produce data that can power unique machine learning solutions. You will learn to build a variety of applications that demonstrate the capabilities of the Google Cloud Platform machine learning API, including data visualizationfor Java; document classification using the Weka ML environment; audio file classification for Android using ML with spectrogram voice data; and machine learning using device sensor data.After reading this book, you will come away with case study examples and projects that you can take away as templates for re-use and exploration for your own machine learning programming projects with Java.What You Will LearnIdentify, organize, and architect the data required for ML projectsDeploy ML solutions in conjunction with cloud providers such as Google and AmazonDetermine which algorithm is the most appropriate for a specific ML problemImplement Java ML solutions on Android mobile devicesCreate Java ML solutions to work with sensor dataBuild Java streaming based solutionsWho This Book Is ForExperienced Java developers who have not implemented machine learning techniques before.…

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Paperback. Condizione: New. Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. Practical Java Machine Learning helps you understand the importance of data and how to organize it for use within your ML project. You will be introduced to tools which can help you identify and manage your data including JSON, visualization, NoSQL databases, and cloud platforms including Google Cloud Platform and Amazon Web Services.Practical Java Machine Learning includes multiple projects, with particular focus on the Android mobile platform and features such as sensors, camera, and connectivity, each of which produce data that can power unique machine learning solutions. You will learn to build a variety of applications that demonstrate the capabilities of the Google Cloud Platform machine learning API, including data visualizationfor Java; document classification using the Weka ML environment; audio file classification for Android using ML with spectrogram voice data; and machine learning using device sensor data.After reading this book, you will come away with case study examples and projects that you can take away as templates for re-use and exploration for your own machine learning programming projects with Java.What You Will LearnIdentify, organize, and architect the data required for ML projectsDeploy ML solutions in conjunction with cloud providers such as Google and AmazonDetermine which algorithm is the most appropriate for a specific ML problemImplement Java ML solutions on Android mobile devicesCreate Java ML solutions to work with sensor dataBuild Java streaming based solutionsWho This Book Is ForExperienced Java developers who have not implemented machine learning techniques before.…

Taschenbuch. Condizione: Neu. Practical Java Machine Learning | Projects with Google Cloud Platform and Amazon Web Services | Mark Wickham | Taschenbuch | xxiii | Englisch | 2018 | Apress | EAN 9781484239506 | 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. …

Paperback. Condizione: New. Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. Practical Java Machine Learning helps you understand the importance of data and how to organize it for use within your ML project. You will be introduced to tools which can help you identify and manage your data including JSON, visualization, NoSQL databases, and cloud platforms including Google Cloud Platform and Amazon Web Services.Practical Java Machine Learning includes multiple projects, with particular focus on the Android mobile platform and features such as sensors, camera, and connectivity, each of which produce data that can power unique machine learning solutions. You will learn to build a variety of applications that demonstrate the capabilities of the Google Cloud Platform machine learning API, including data visualizationfor Java; document classification using the Weka ML environment; audio file classification for Android using ML with spectrogram voice data; and machine learning using device sensor data.After reading this book, you will come away with case study examples and projects that you can take away as templates for re-use and exploration for your own machine learning programming projects with Java.What You Will LearnIdentify, organize, and architect the data required for ML projectsDeploy ML solutions in conjunction with cloud providers such as Google and AmazonDetermine which algorithm is the most appropriate for a specific ML problemImplement Java ML solutions on Android mobile devicesCreate Java ML solutions to work with sensor dataBuild Java streaming based solutionsWho This Book Is ForExperienced Java developers who have not implemented machine learning techniques before.…

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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. Practical Java Machine Learning helps you understand the importance of data and how to organize it for use within your ML project. You will be introduced to tools which can help you identify and manage your data including JSON, visualization, NoSQL databases, and cloud platforms including Google Cloud Platform and Amazon Web Services.Practical Java Machine Learning includes multiple projects, with particular focus on the Android mobile platform and features such as sensors, camera, and connectivity, each of which produce data that can power unique machine learning solutions. You will learn to build a variety of applications that demonstrate the capabilities of the Google Cloud Platform machine learning API, including data visualization for Java; document classification using the Weka ML environment; audio file classification for Android using ML with spectrogram voice data; and machine learning using device sensor data.After reading this book, you will come away with case study examples and projects that you can take away as templates for re-use and exploration for your own machine learning programming projects with Java.What You Will LearnIdentify, organize, and architect the data required for ML projectsDeploy ML solutions in conjunction with cloud providers such as Google and AmazonDetermine which algorithm is the most appropriate for a specific ML problemImplement Java ML solutions on Android mobile devicesCreate Java ML solutions to work with sensor dataBuild Java streaming based solutionsWho This Book Is ForExperienced Java developers who have not implemented machine learning techniques before. 416 pp. Englisch.…

Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. A practical, hands-on book covering the latest machine learning and cloud techniques that Java developers can useExplains why machine learning techniques can yield new functionality which was not previously possible using .…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. Practical Java Machine Learning helps you understand the importance of data and how to organize it for use within your ML project. You will be introduced to tools which can help you identify and manage your data including JSON, visualization, NoSQL databases, and cloud platforms including Google Cloud Platform and Amazon Web Services.Practical Java Machine Learning includes multiple projects, with particular focus on the Android mobile platform and features such as sensors, camera, and connectivity, each of which produce data that can power unique machine learning solutions. You will learn to build a variety of applications that demonstrate the capabilities of the Google Cloud Platform machine learning API, including data visualizationfor Java; document classification using the Weka ML environment; audio file classification for Android using ML with spectrogram voice data; and machine learning using device sensor data.After reading this book, you will come away with case study examples and projects that you can take away as templates for re-use and exploration for your own machine learning programming projects with Java.What You Will LearnIdentify, organize, and architect the data required for ML projectsDeploy ML solutions in conjunction with cloud providers such as Google and AmazonDetermine which algorithm is the most appropriate for a specific ML problemImplement Java ML solutions on Android mobile devicesCreate Java ML solutions to work with sensor dataBuild Java streaming based solutionsWho This Book Is ForExperienced Java developers who have not implemented machine learning techniques before. …

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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. Practical Java Machine Learning helps you understand the importance of data and how to organize it for use within your ML project. You will be introduced to tools which can help you identify and manage your data including JSON, visualization, NoSQL databases, and cloud platforms including Google Cloud Platform and Amazon Web Services.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 416 pp. Englisch. …