Introduction to Amazon Web Services Beginner s Guide Book

Author: George Sammons
Publisher: Createspace Independent Publishing Platform
ISBN: 9781539751953
Format: PDF, ePub
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This book is a guide to AWs (Amazon Web Services). It begins by guiding you on how to perform error retries. Sometimes, requests made to AWS may fail, and this calls for you to retry sending the requests. However, you should make the maximum number of retries and some other parameters. These are discussed in this book. The best security credentials for use in AWS are examined, so you will know the best practices for ensuring that these are secure. The AWS requests also need to be signed, which is a good way for ensuring that the requests are not tampered with while in transit. This book guides you on how to sign both AWS requests and the AWS API requests. You will also learn how to verify whether the request was interfered with or not on the receiving end. The ARN (Amazon Resource Name) and namespaces, which are used for the purpose of uniquely identifying resources are explored in this book. The process of using Unbound guidelines for the purpose of auditing the security of your AWS services is also discussed. The book also provides you with a guide on how to set up DNS Resolution between AWS and On-Premises Networks. The following topics are discussed in this book: - Error Retries in AWS - AWS Security Credentials - Setting Up DNS Resolution Between AWS and On-Premises Networks Using Unbound - Guidelines for Security Audit - AWS Service Namaspace and Amazon Resource Names (ARN) - How to Sign AWS API Requests

Effective Amazon Machine Learning

Author: Alexis Perrier
Publisher: Packt Publishing Ltd
ISBN: 1785881795
Format: PDF, ePub, Mobi
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Learn to leverage Amazon's powerful platform for your predictive analytics needs About This Book Create great machine learning models that combine the power of algorithms with interactive tools without worrying about the underlying complexity Learn the What's next? of machine learning—machine learning on the cloud—with this unique guide Create web services that allow you to perform affordable and fast machine learning on the cloud Who This Book Is For This book is intended for data scientists and managers of predictive analytics projects; it will teach beginner- to advanced-level machine learning practitioners how to leverage Amazon Machine Learning and complement their existing Data Science toolbox. No substantive prior knowledge of Machine Learning, Data Science, statistics, or coding is required. What You Will Learn Learn how to use the Amazon Machine Learning service from scratch for predictive analytics Gain hands-on experience of key Data Science concepts Solve classic regression and classification problems Run projects programmatically via the command line and the Python SDK Leverage the Amazon Web Service ecosystem to access extended data sources Implement streaming and advanced projects In Detail Predictive analytics is a complex domain requiring coding skills, an understanding of the mathematical concepts underpinning machine learning algorithms, and the ability to create compelling data visualizations. Following AWS simplifying Machine learning, this book will help you bring predictive analytics projects to fruition in three easy steps: data preparation, model tuning, and model selection. This book will introduce you to the Amazon Machine Learning platform and will implement core data science concepts such as classification, regression, regularization, overfitting, model selection, and evaluation. Furthermore, you will learn to leverage the Amazon Web Service (AWS) ecosystem for extended access to data sources, implement realtime predictions, and run Amazon Machine Learning projects via the command line and the Python SDK. Towards the end of the book, you will also learn how to apply these services to other problems, such as text mining, and to more complex datasets. Style and approach This book will include use cases you can relate to. In a very practical manner, you will explore the various capabilities of Amazon Machine Learning services, allowing you to implementing them in your environment with consummate ease.

Docker

Author: Andy Hayes
Publisher: Createspace Independent Publishing Platform
ISBN: 9781542739047
Format: PDF, Kindle
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Docker - A Quick Start Beginners Guide Welcome to "Docker: A Quick Introduction To Using Docker Containers Today." This is the best guide for people who want to use Docker as well as implement container-based virtualization. You should not shy away from Docker containers because you lack the knowledge to implement them. All you have to do is completely engage this book. We have divided the book into chapters to make it easier for you to go through. The different topics covered are: Playing with Busybox Docker Run Terminology Webapps with Docker Static Sites Docker Images Our First Image Dockerfile Docker on AWS & much more Take Action Today and Learn Docker In No Time! Click the "Buy now with 1-Click" to the right and get this guide immediately.