Provide solutions to all your Amazon EC2, SQS, Kinesis, and S3 problems, including implementation using the AWS Management Console, AWS CLI, and AWS SDK (Java). You'll find recipes on implementation and configuration of Amazon EC2, SQS, Kinesis, and S3 along with the code snippets and AWS CLI commands. Practical Amazon EC2, SQS, Kinesis, and S3 uses focused examples that include only the details you need to get things done. You'll see production use cases of Amazon EC2, SQS, Kinesis, and S3 and how to implement cloud watch in projects for these services. Learn how to raise an alarm on Amazon EC2, SQS, Kinesis, and S3 as part of a continuous monitoring system designed to increase performance and avoid side effects in your services. What You'll Learn Manage Amazon EC2, SQS, Kinesis, and S3 using the AWS Management Console Use the AWS CLI Employ the AWS Java SDK Configure alarms on Amazon EC2, SQS, Kinesis, and S3 Who This Book Is For Software developers and architects, system engineers, and project managers

Provide solutions to all your Amazon EC2, SQS, Kinesis, and S3 problems, including implementation using the AWS Management Console, AWS CLI, and AWS SDK (Java). You'll find recipes on implementation and configuration of Amazon EC2, SQS, Kinesis, and S3 along with the code snippets and AWS CLI commands. Practical Amazon EC2, SQS, Kinesis, and S3 uses focused examples that include only the details you need to get things done. You'll see production use cases of Amazon EC2, SQS, Kinesis, and S3 and how to implement cloud watch in projects for these services. Learn how to raise an alarm on Amazon EC2, SQS, Kinesis, and S3 as part of a continuous monitoring system designed to increase performance and avoid side effects in your services. What You'll Learn Manage Amazon EC2, SQS, Kinesis, and S3 using the AWS Management Console Use the AWS CLI Employ the AWS Java SDK Configure alarms on Amazon EC2, SQS, Kinesis, and S3 Who This Book Is For Software developers and architects, system engineers, and project managers

AWS Certification Guide - AWS Certified Machine Learning – Specialty Unleash the Potential of AWS Machine Learning Embark on a comprehensive journey into the world of machine learning on AWS with this essential guide, tailored for those pursuing the AWS Certified Machine Learning – Specialty certification. This book is a valuable resource for professionals seeking to harness the power of AWS for machine learning applications. Inside, You'll Explore: Foundational to Advanced ML Concepts: Understand the breadth of AWS machine learning services and tools, from SageMaker to DeepLens, and learn how to apply them in various scenarios. Practical Machine Learning Scenarios: Delve into real-world examples and case studies, illustrating the practical applications of AWS machine learning technologies in different industries. Targeted Exam Preparation: Navigate the certification exam with confidence, thanks to detailed insights into the exam format, including specific chapters aligned with the certification objectives and comprehensive practice questions. Latest Trends and Best Practices: Stay at the forefront of machine learning advancements with up-to-date coverage of the latest AWS features and industry best practices. Written by a Machine Learning Expert Authored by an experienced practitioner in AWS machine learning, this guide combines in-depth knowledge with practical insights, providing a rich and comprehensive learning experience. Your Comprehensive Resource for ML Certification Whether you are deepening your existing machine learning skills or embarking on a new specialty in AWS, this book is your definitive companion, offering an in-depth exploration of AWS machine learning services and preparing you for the Specialty certification exam. Advance Your Machine Learning Career Beyond preparing for the exam, this guide is about mastering the complexities of AWS machine learning. It's a pathway to developing expertise that can be applied in innovative and transformative ways across various sectors. Start Your Specialized Journey in AWS Machine Learning Set off on your path to becoming an AWS Certified Machine Learning specialist. This guide is your first step towards mastering AWS machine learning and unlocking new opportunities in this exciting and rapidly evolving field. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

Amazon Web Services (AWS) provides on-demand cloud computing platforms and application programming interfaces (APIs) to individuals, companies, and govern- ments, along with distributed computing processing capacity and software tools via AWS server farms. This text presents a hands-on approach for beginners to get started with Amazon Web Services (AWS) in a simple way. Key Features It discusses topics such as Amazon Elastic Compute Cloud, Elastic Load Balancing, Auto Scaling Groups, and Amazon Simple Storage Service. It showcases Amazon Web Services’ identity, access management resources, and attribute-based access control. It covers serverless computing services, Virtual Private Cloud, Amazon Aurora, and Amazon Comprehend. It explains Amazon Web Services Free Tier, Amazon Web Services Marketplace, and Amazon Elastic Container Service. It includes security in Amazon Web Services, the shared responsibilitymodel, and high-performance computing on Amazon Web Services. The text is primarily written for graduate students, professionals, and academic researchers working in the fields of computer science, engineering, and information technology. Parul Dubey is currently working as an Assistant professor in the Department of Artificial Intelligence at G H Raisoni College of Engineering, Nagpur, India. She has filed for 15 Indian patents. She is responsible for about 10 publications in conference proceedings, Scopus, and journals. She has contributed book chapters in an edited book published by CRC Press and other reputed publishers. She is also an AWS Certified Cloud Practitioner. Rohit Raja is working as an associate professor and head in the Department of Information Technology at Guru Ghasidas Vishwavidyalaya, Bilaspur, India. His research interests include facial recognition, signal processing, networking, and data mining. He has pub- lished 100 research papers in various international and national journals (including publications by the IEEE, Springer, etc.) and proceedings of reputed international and national conferences (again including publications by Springer and the IEEE).

This fast-paced guide will quickly enhance your skills to develop a highly scalable Cloud environment Key Features Efficiently build a highly scalable and reliable cloud environment for your applications with AWS Leverage the various AWS components and services to build a secure, reliable, and robust environment to host your applications on This quick-start guide will quickly enhance your skills to develop highly scalable services Book Description AWS is at the forefront of Cloud Computing today. Businesses are adopting AWS Cloud because of its reliability, versatility, and flexible design. The main focus of this book is teaching you how to build and manage highly reliable and scalable applications and services on AWS. It will provide you with all the necessary skills to design, deploy, and manage your applications and services on the AWS cloud platform. We’ll start by exploring Amazon S3, EC2, and so on to get you well-versed with core Amazon services. Moving on, we’ll teach you how to design and deploy highly scalable and optimized workloads. You’ll also discover easy-to-follow, hands-on steps, tips, and recommendations throughout the book and get to know essential security and troubleshooting concepts. By the end of the book, you’ll be able to create a highly secure, fault tolerant, and scalable environment for your applications to run on. What you will learn Find out about IAM to access AWS services securely Explore EC2 (virtual server) and scale up/down your application based on heavy traffic Learn about unlimited data storage service S3 and host a static website within minutes Get to grips with Relational Databases and NoSQL databases under the AWS ecosystem Understand the caching mechanism Get to know about notifications service and monitor AWS services Secure and troubleshoot your AWS architecture Who this book is for This book is for IT professionals and system administrators looking to design, deploy, and manage your applications and services on the AWS cloud platform. It’s also ideal for developers looking to build highly scalable cloud-based services. A basic understanding of AWS would be beneficial.

The advancements in intelligent decision-making techniques have elevated the efficiency of manufacturing industries and led to the start of the Industry 4.0 era. Industry 4.0 is revolutionizing the way companies manufacture, improve, and distribute their products. Manufacturers are integrating new technologies, including the Internet of Things (IoT), cloud computing and analytics, and artificial intelligence and machine learning, into their production facilities throughout their operations. In the past few years, intelligent analytics has emerged as a solution that examines both historical and real-time data to uncover performance insights. Because the amount of data that needs analysis is growing daily, advanced technologies are necessary to collect, arrange, and analyze incoming data. This approach enables businesses to detect valuable connections and trends and make decisions that boost overall performance. In Industry 4.0, intelligent analytics has a broader scope in terms of descriptive, predictive, and prescriptive subdomains. To this end, the book will aim to review and highlight the challenges faced by intelligent analytics in Industry 4.0 and present the recent developments done to address those challenges.

This book provides techniques for the deployment of semantic technologies in data analysis along with the latest applications across the field such as Internet of Things (IoT). The authors focus on the use of the IoT and big data in business intelligence, data management, Hadoop, machine learning, cloud, smart cities, etc. They discuss how the generation of big data by IoT has ruptured the existing data processing capacity of IoT and recommends the adoption of data analytics to strengthen solutions. The book addresses the challenges in designing the web based IoT system, provides a comparative analysis of different advanced approaches in industries, and contains an analysis of databases to provide expert systems. The book aims to bring together leading academic scientists, researchers, and research scholars to exchange and share their experiences and research results on all aspects of IoT and big data analytics.