Machine learning in the aws cloud : add intelligence to applications with amazon sagemaker and amazon rekognition
Put the power of AWS Cloud machine learning services to work in your business and commercial applications! Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regressio...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Mishra, Abhishek [verfasserIn] |
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| Format: |
E-Book |
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| Sprache: |
Englisch |
| Erschienen: |
San Francisco, Calif: Sybex, a Wiley Brand ; 2019 |
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| Schlagwörter: | |
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| Schlagwörter: |
| Umfang: |
1 Online-Ressource (xxvii, 499 Seiten) ; Illustrationen, Diagramme |
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| Weitere Ausgabe: |
Erscheint auch als Druck-Ausgabe Mishra, Abhishek: Machine learning in the AWS cloud - Indianapolis, Indiana : Sybex, a Wiley Brand, 2019 |
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| Links: | |
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| ISBN: |
978-1-119-55672-5 978-1-119-55674-9 978-1-119-55673-2 |
| DOI / URN: |
10.1002/9781119556749 |
|---|
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| 520 | |a Put the power of AWS Cloud machine learning services to work in your business and commercial applications! Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services. Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You'll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you'll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems. - Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building - Discover common neural network frameworks with Amazon SageMaker - Solve computer vision problems with Amazon Rekognition - Benefit from illustrations, source code examples, and sidebars in each chapter The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem | ||
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| abstract |
Put the power of AWS Cloud machine learning services to work in your business and commercial applications! Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services. Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You'll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you'll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems. - Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building - Discover common neural network frameworks with Amazon SageMaker - Solve computer vision problems with Amazon Rekognition - Benefit from illustrations, source code examples, and sidebars in each chapter The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem |
| abstractGer |
Put the power of AWS Cloud machine learning services to work in your business and commercial applications! Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services. Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You'll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you'll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems. - Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building - Discover common neural network frameworks with Amazon SageMaker - Solve computer vision problems with Amazon Rekognition - Benefit from illustrations, source code examples, and sidebars in each chapter The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem |
| abstract_unstemmed |
Put the power of AWS Cloud machine learning services to work in your business and commercial applications! Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services. Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You'll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you'll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems. - Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building - Discover common neural network frameworks with Amazon SageMaker - Solve computer vision problems with Amazon Rekognition - Benefit from illustrations, source code examples, and sidebars in each chapter The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem |
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Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services. Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You'll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you'll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems. - Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building - Discover common neural network frameworks with Amazon SageMaker - Solve computer vision problems with Amazon Rekognition - Benefit from illustrations, source code examples, and sidebars in each chapter The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem Amazon Web Services (Firm) Amazon Web Services (Firm) Machine learning Cloud computing COMPUTERS / Machine Theory Apprentissage automatique Infonuagique Cloud computing Machine learning s (DE-588)7623494-0 (DE-627)577000314 (DE-576)285431765 Cloud Computing gnd s (DE-588)4193754-5 (DE-627)105224782 (DE-576)21008944X Maschinelles Lernen gnd s (DE-588)1143985591 (DE-627)1003548369 (DE-576)495234362 Amazon Web Services gnd (DE-627) 9781119556718 Erscheint auch als Druck-Ausgabe Mishra, Abhishek Machine learning in the AWS cloud Indianapolis, Indiana : Sybex, a Wiley Brand, 2019 xxvii, 499 Seiten (DE-627)1762812800 9781119556718 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119556749 X:WILEY Verlag lizenzpflichtig https://doi.org/10.1002/9781119556749 X:WILEY Verlag lizenzpflichtig BSZ-35-UBC-S2AAFH ZDB-35-UBC ZDB-35-WIC GBV_ILN_62 ISIL_DE-28 SYSFLAG_1 GBV_KXP GBV_ILN_120 ISIL_DE-715 GBV_ILN_285 ISIL_DE-517 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2001 ISIL_DE-21 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2111 ISIL_DE-944 54.72 Künstliche Intelligenz SEPA (DE-627)10641240X 54.80 Angewandte Informatik SEPA (DE-627)106417967 BO 045F 006.3/1 62 01 0028 3618161158 OLR-Wiley-EBS Vervielfältigungen (z.B. 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Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services. Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You'll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you'll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems. - Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building - Discover common neural network frameworks with Amazon SageMaker - Solve computer vision problems with Amazon Rekognition - Benefit from illustrations, source code examples, and sidebars in each chapter The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem Amazon Web Services (Firm) Amazon Web Services (Firm) Machine learning Cloud computing COMPUTERS / Machine Theory Apprentissage automatique Infonuagique Cloud computing Machine learning s (DE-588)7623494-0 (DE-627)577000314 (DE-576)285431765 Cloud Computing gnd s (DE-588)4193754-5 (DE-627)105224782 (DE-576)21008944X Maschinelles Lernen gnd s (DE-588)1143985591 (DE-627)1003548369 (DE-576)495234362 Amazon Web Services gnd (DE-627) 9781119556718 Erscheint auch als Druck-Ausgabe Mishra, Abhishek Machine learning in the AWS cloud Indianapolis, Indiana : Sybex, a Wiley Brand, 2019 xxvii, 499 Seiten (DE-627)1762812800 9781119556718 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119556749 X:WILEY Verlag lizenzpflichtig https://doi.org/10.1002/9781119556749 X:WILEY Verlag lizenzpflichtig BSZ-35-UBC-S2AAFH ZDB-35-UBC ZDB-35-WIC GBV_ILN_62 ISIL_DE-28 SYSFLAG_1 GBV_KXP GBV_ILN_120 ISIL_DE-715 GBV_ILN_285 ISIL_DE-517 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2001 ISIL_DE-21 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2111 ISIL_DE-944 54.72 Künstliche Intelligenz SEPA (DE-627)10641240X 54.80 Angewandte Informatik SEPA (DE-627)106417967 BO 045F 006.3/1 62 01 0028 3618161158 OLR-Wiley-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. Temporär im Bestand der UB Rostock z 02-04-20 120 01 0715 3905799839 00 --%%-- --%%-- g --%%-- alma z 10-04-21 285 01 0517 4049409887 OLR-Wiley-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 05-01-23 370 01 4370 3671109084 EBS Wiley gelöscht Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. 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Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services. Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You'll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you'll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems. - Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building - Discover common neural network frameworks with Amazon SageMaker - Solve computer vision problems with Amazon Rekognition - Benefit from illustrations, source code examples, and sidebars in each chapter The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem Amazon Web Services (Firm) Amazon Web Services (Firm) Machine learning Cloud computing COMPUTERS / Machine Theory Apprentissage automatique Infonuagique Cloud computing Machine learning s (DE-588)7623494-0 (DE-627)577000314 (DE-576)285431765 Cloud Computing gnd s (DE-588)4193754-5 (DE-627)105224782 (DE-576)21008944X Maschinelles Lernen gnd s (DE-588)1143985591 (DE-627)1003548369 (DE-576)495234362 Amazon Web Services gnd (DE-627) 9781119556718 Erscheint auch als Druck-Ausgabe Mishra, Abhishek Machine learning in the AWS cloud Indianapolis, Indiana : Sybex, a Wiley Brand, 2019 xxvii, 499 Seiten (DE-627)1762812800 9781119556718 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119556749 X:WILEY Verlag lizenzpflichtig https://doi.org/10.1002/9781119556749 X:WILEY Verlag lizenzpflichtig BSZ-35-UBC-S2AAFH ZDB-35-UBC ZDB-35-WIC GBV_ILN_62 ISIL_DE-28 SYSFLAG_1 GBV_KXP GBV_ILN_120 ISIL_DE-715 GBV_ILN_285 ISIL_DE-517 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2001 ISIL_DE-21 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2111 ISIL_DE-944 54.72 Künstliche Intelligenz SEPA (DE-627)10641240X 54.80 Angewandte Informatik SEPA (DE-627)106417967 BO 045F 006.3/1 62 01 0028 3618161158 OLR-Wiley-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. Temporär im Bestand der UB Rostock z 02-04-20 120 01 0715 3905799839 00 --%%-- --%%-- g --%%-- alma z 10-04-21 285 01 0517 4049409887 OLR-Wiley-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 05-01-23 370 01 4370 3671109084 EBS Wiley gelöscht Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. 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Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services. Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You'll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you'll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems. - Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building - Discover common neural network frameworks with Amazon SageMaker - Solve computer vision problems with Amazon Rekognition - Benefit from illustrations, source code examples, and sidebars in each chapter The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem Amazon Web Services (Firm) Amazon Web Services (Firm) Machine learning Cloud computing COMPUTERS / Machine Theory Apprentissage automatique Infonuagique Cloud computing Machine learning s (DE-588)7623494-0 (DE-627)577000314 (DE-576)285431765 Cloud Computing gnd s (DE-588)4193754-5 (DE-627)105224782 (DE-576)21008944X Maschinelles Lernen gnd s (DE-588)1143985591 (DE-627)1003548369 (DE-576)495234362 Amazon Web Services gnd (DE-627) 9781119556718 Erscheint auch als Druck-Ausgabe Mishra, Abhishek Machine learning in the AWS cloud Indianapolis, Indiana : Sybex, a Wiley Brand, 2019 xxvii, 499 Seiten (DE-627)1762812800 9781119556718 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119556749 X:WILEY Verlag lizenzpflichtig https://doi.org/10.1002/9781119556749 X:WILEY Verlag lizenzpflichtig BSZ-35-UBC-S2AAFH ZDB-35-UBC ZDB-35-WIC GBV_ILN_62 ISIL_DE-28 SYSFLAG_1 GBV_KXP GBV_ILN_120 ISIL_DE-715 GBV_ILN_285 ISIL_DE-517 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2001 ISIL_DE-21 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2111 ISIL_DE-944 54.72 Künstliche Intelligenz SEPA (DE-627)10641240X 54.80 Angewandte Informatik SEPA (DE-627)106417967 BO 045F 006.3/1 62 01 0028 3618161158 OLR-Wiley-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. Temporär im Bestand der UB Rostock z 02-04-20 120 01 0715 3905799839 00 --%%-- --%%-- g --%%-- alma z 10-04-21 285 01 0517 4049409887 OLR-Wiley-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 05-01-23 370 01 4370 3671109084 EBS Wiley gelöscht Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 25-05-20 2001 01 DE-21 3819399623 00 --%%-- --%%-- --%%-- n l01 08-12-20 2020 01 DE-Ch1 4046980451 00 --%%-- --%%-- --%%-- n Campuslizenz l01 28-01-22 2111 01 DE-944 3819399666 00 --%%-- eBook Wiley --%%-- n Elektronischer Volltext - Campuslizenz l01 08-12-20 2111 02 DE-944 3952327662 00 --%%-- E-Book Wiley --%%-- n Elektronischer Volltext - Campuslizenz l02 15-07-21 62 01 0028 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119556749 120 01 0715 http://49gbv-uob-primo.hosted.exlibrisgroup.com/openurl/49GBV_UOB/UOB_services_page?u.ignore_date_coverage=true&rft.mms_id=991015328550403501 285 01 0517 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119556749 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://onlinelibrary.wiley.com/doi/book/10.1002/9781119556749 2001 01 DE-21 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119556749 2020 01 DE-Ch1 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119556749 2111 01 DE-944 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119556749 2111 02 DE-944 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119556749 2001 01 DE-21 00 s eBook-Wiley-UBCM-eBook-Collection-2018 2111 01 DE-944 00 (DE-627)1353370437 e-Book 2111 02 DE-944 00 (DE-627)1353370437 e-Book 62 01 0028 OLR-Wiley-EBS 120 01 0715 alma 285 01 0517 OLR-Wiley-EBS 370 01 4370 EBS Wiley gelöscht 370 01 4370 olr-ebook wiley 370 01 4370 ACQ |
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9781119556725 electronic bk. 978-1-119-55672-5 9781119556749 electronic bk. : oBook 978-1-119-55674-9 9781119556732 electronic bk. 978-1-119-55673-2 10.1002/9781119556749 doi EB00764700 (DE-627)1691165514 (DE-599)KEP049968866 (OCoLC)1182811504 (WILEY)9781119556749 (EBP)049968866 DE-627 ger DE-627 rakwb eng XD-US Q325.5 006.3/1 54.72 bkl 54.80 bkl Mishra, Abhishek verfasserin (DE-588)1084799820 (DE-627)848722434 (DE-576)45684290X aut Machine learning in the aws cloud add intelligence to applications with amazon sagemaker and amazon rekognition Abhishek Mishra San Francisco, Calif Sybex, a Wiley Brand 2019 1 Online-Ressource (xxvii, 499 Seiten) Illustrationen, Diagramme Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Put the power of AWS Cloud machine learning services to work in your business and commercial applications! Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services. Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You'll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you'll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems. - Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building - Discover common neural network frameworks with Amazon SageMaker - Solve computer vision problems with Amazon Rekognition - Benefit from illustrations, source code examples, and sidebars in each chapter The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem Amazon Web Services (Firm) Amazon Web Services (Firm) Machine learning Cloud computing COMPUTERS / Machine Theory Apprentissage automatique Infonuagique Cloud computing Machine learning s (DE-588)7623494-0 (DE-627)577000314 (DE-576)285431765 Cloud Computing gnd s (DE-588)4193754-5 (DE-627)105224782 (DE-576)21008944X Maschinelles Lernen gnd s (DE-588)1143985591 (DE-627)1003548369 (DE-576)495234362 Amazon Web Services gnd (DE-627) 9781119556718 Erscheint auch als Druck-Ausgabe Mishra, Abhishek Machine learning in the AWS cloud Indianapolis, Indiana : Sybex, a Wiley Brand, 2019 xxvii, 499 Seiten (DE-627)1762812800 9781119556718 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119556749 X:WILEY Verlag lizenzpflichtig https://doi.org/10.1002/9781119556749 X:WILEY Verlag lizenzpflichtig BSZ-35-UBC-S2AAFH ZDB-35-UBC ZDB-35-WIC GBV_ILN_62 ISIL_DE-28 SYSFLAG_1 GBV_KXP GBV_ILN_120 ISIL_DE-715 GBV_ILN_285 ISIL_DE-517 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2001 ISIL_DE-21 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2111 ISIL_DE-944 54.72 Künstliche Intelligenz SEPA (DE-627)10641240X 54.80 Angewandte Informatik SEPA (DE-627)106417967 BO 045F 006.3/1 62 01 0028 3618161158 OLR-Wiley-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. Temporär im Bestand der UB Rostock z 02-04-20 120 01 0715 3905799839 00 --%%-- --%%-- g --%%-- alma z 10-04-21 285 01 0517 4049409887 OLR-Wiley-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 05-01-23 370 01 4370 3671109084 EBS Wiley gelöscht Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. 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Book |
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Künstliche Intelligenz Angewandte Informatik |
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findex.gbv.de |
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62@ 120@ 285@ 370@ 2001@01 2020@01 2111@01 2111@02 |
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006.3/1 |
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Mishra, Abhishek @@aut@@ |
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