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Machine learning in the AWS Cloud : ...

Amazon Web Services (Firm)

Machine learning in the AWS Cloud : = add intelligence to applications with Amazon SageMaker and Amazon Rekognition /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Machine learning in the AWS Cloud :/ Abhishek Mishra.
Reminder of title:	add intelligence to applications with Amazon SageMaker and Amazon Rekognition /
remainder title:	Machine learning in the Amazon Web Services Cloud
Author:	Mishra, Abhishek.
Published:	Indianapolis, Indiana :John Wiley & Sons, Inc., : c2019.,
Description:	xxvii, 499p. :ill. ; : 24cm.;
Notes:	Includes index.
Subject:	Machine learning. -
ISBN:	9781119556718 (pbk.) :

Machine learning in the AWS Cloud : = add intelligence to applications with Amazon SageMaker and Amazon Rekognition /
Mishra, Abhishek.

Machine learning in the AWS Cloud :add intelligence to applications with Amazon SageMaker and Amazon Rekognition /Machine learning in the Amazon Web Services CloudAbhishek Mishra. - Indianapolis, Indiana :John Wiley & Sons, Inc.,c2019. - xxvii, 499p. :ill. ;24cm.

Includes index.

Part 1. Fundamentals of machine learning. Introduction to machine learning -- Data collection and preprocessing -- Data visualization with Python -- Creating machine learning models with Scikit-learn -- Evaluating machine learning models -- Part 2. Machine learning with Amazon Web Services. Introduction to Amazon Web Services -- AWS global infrastructure -- Identity and access management -- Amazon S3 -- Amazon Cognito -- Amazon DynamoDB -- AWS Lambda -- Amazon Comprehend -- Amazon Lex -- Amazon machine learning -- Amazon SageMaker -- Using Google TensorFlow with Amazon SageMaker -- Amazon Rekognition -- Appendix A. Anaconda and Jupyter Notebook setup -- Appendix B. AWS resources needed to use this book -- Appendix C. Installing and configuring the AWS CLI -- Appendix D. Introduction to NumPy and Pandas.

Recent advances in storage, CPU, and GPU technology, coupled with the ease with which you can create virtual computing resources in the cloud, and the availability of Python libraries such as Pandas, Matplotlib, TensorFlow, and Scikit-learn, have made it possible to build and deploy machine learning (ML) systems at scale and get results in real-time. "Machine learning in the AWS Cloud" offers an introduction to the machine learning capabilities of the Amazon Web Services ecosystem. The book is filled with illustrative examples that are designed to help with solutions to real-world regression and classification challenges. While prior experience with ML is not a requirement, some knowledge of Python and a basic knowledge of Amazon Web Services is a plus.

ISBN: 9781119556718 (pbk.) :NT1516Subjects--Corporate Names:

1142271
Amazon Web Services (Firm)
Subjects--Topical Terms:

561253
Machine learning.

LC Class. No.: Q325.5 / .M57 2019

Dewey Class. No.: 006.3/1

Machine learning in the AWS Cloud : = add intelligence to applications with Amazon SageMaker and Amazon Rekognition /
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520 # $a Recent advances in storage, CPU, and GPU technology, coupled with the ease with which you can create virtual computing resources in the cloud, and the availability of Python libraries such as Pandas, Matplotlib, TensorFlow, and Scikit-learn, have made it possible to build and deploy machine learning (ML) systems at scale and get results in real-time. "Machine learning in the AWS Cloud" offers an introduction to the machine learning capabilities of the Amazon Web Services ecosystem. The book is filled with illustrative examples that are designed to help with solutions to real-world regression and classification challenges. While prior experience with ML is not a requirement, some knowledge of Python and a basic knowledge of Amazon Web Services is a plus.
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