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Machine Learning in the AWS Cloud

Add Intelligence to Applications with Amazon Sagemaker and Amazon Rekognition

Abhishek Mishra
Livre broché | Anglais
69,45 €
+ 138 points
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Livraison en Belgique: 3,99 €
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Description

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.

Spécifications

Parties prenantes

Auteur(s) :
Editeur:

Contenu

Nombre de pages :
528
Langue:
Anglais

Caractéristiques

EAN:
9781119556718
Date de parution :
11-09-19
Format:
Livre broché
Format numérique:
Trade paperback (VS)
Dimensions :
185 mm x 234 mm
Poids :
839 g

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