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Machine Learning In The Aws Cloud eBook

Add Intelligence To Applications With Amazon Sagemaker And Amazon Rekognition

by Abhishek Mishra
language: english
Publisher: WILEY, August of 2019 ‧
50,34€
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Ebook for ADE
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.

Machine Learning In The Aws Cloud

Add Intelligence To Applications With Amazon Sagemaker And Amazon Rekognition

by Abhishek Mishra

Property Description
ISBN: 9781119556732
Publisher: WILEY
Release Date: August of 2019
Language: English
Format: eBook
File Format and Compatibility: PDF para ADE
Categories: eBooks in English > Computing > Other Applications
EAN: 9781119556732