Machine Learning in the AWS Cloud
Add Intelligence to Applications with Amazon SageMaker and AmazonRekognition
1. Edition October 2019
528 Pages, Softcover
Practical Approach Book
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.
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
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.