John Wiley & Sons Machine Learning in the AWS Cloud Cover Put the power of AWS Cloud machine learning services to work in your business and commercial applica.. Product #: 978-1-119-55671-8 Regular price: $42.90 $42.90 In Stock

Machine Learning in the AWS Cloud

Add Intelligence to Applications with Amazon SageMaker and Amazon Rekognition

Mishra, Abhishek

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1. Edition October 2019
528 Pages, Softcover
Practical Approach Book

ISBN: 978-1-119-55671-8
John Wiley & Sons

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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.

Introduction xxiii

Part 1 Fundamentals of Machine Learning 1

Chapter 1 Introduction to Machine Learning 3

Chapter 2 Data Collection and Preprocessing 27

Chapter 3 Data Visualization with Python 51

Chapter 4 Creating Machine Learning Models with Scikit-learn 79

Chapter 5 Evaluating Machine Learning Models 115

Part 2 Machine Learning with Amazon Web Services 133

Chapter 6 Introduction to Amazon Web Services 135

Chapter 7 AWS Global Infrastructure 151

Chapter 8 Identity and Access Management 161

Chapter 9 Amazon S3 181

Chapter 10 Amazon Cognito 201

Chapter 11 Amazon DynamoDB 221

Chapter 12 AWS Lambda 237

Chapter 13 Amazon Comprehend 257

Chapter 14 Amazon Lex 275

Chapter 15 Amazon Machine Learning 317

Chapter 16 Amazon SageMaker 353

Chapter 17 Using Google TensorFlow with Amazon SageMaker 387

Chapter 18 Amazon Rekognition 421

Appendix A Anaconda and Jupyter Notebook Setup 445

Appendix B AWS Resources Needed to Use This Book 455

Appendix C Installing and Configuring the AWS CLI 461

Appendix D Introduction to NumPy and Pandas 467

Index 485
ABOUT THE AUTHOR

ABHISHEK MISHRA has more than 19 years' experience across a broad range of enterprise technologies. He consults as a security and fraud solution architect with Lloyds Banking group PLC in London. He is the author of Amazon Web Services for Mobile Developers.