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This book vividly illustrates all the promising and potential
machine learning (ML) and deep learning (DL) algorithms through a
host of real-world and real-time business use cases. Machines and
devices can be empowered to self-learn and exhibit intelligent
behavior. Also, Big Data combined with real-time and runtime data
can lead to personalized, prognostic, predictive, and prescriptive
insights. This book examines the following topics: Cognitive
machines and devices Cyber physical systems (CPS) The Internet of
Things (IoT) and industrial use cases Industry 4.0 for smarter
manufacturing Predictive and prescriptive insights for smarter
systems Machine vision and intelligence Natural interfaces K-means
clustering algorithm Support vector machine (SVM) algorithm A
priori algorithms Linear and logistic regression Applied Learning
Algorithms for Intelligent IoT clearly articulates ML and DL
algorithms that can be used to unearth predictive and prescriptive
insights out of Big Data. Transforming raw data into information
and relevant knowledge is gaining prominence with the availability
of data processing and mining, analytics algorithms, platforms,
frameworks, and other accelerators discussed in the book. Now, with
the emergence of machine learning algorithms, the field of data
analytics is bound to reach new heights. This book will serve as a
comprehensive guide for AI researchers, faculty members, and IT
professionals. Every chapter will discuss one ML algorithm, its
origin, challenges, and benefits, as well as a sample industry use
case for explaining the algorithm in detail. The book's detailed
and deeper dive into ML and DL algorithms using a practical use
case can foster innovative research.
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Internet of Things - Third International Conference, ICIoT 2022, Chennai, India, April 5–7, 2022, Revised Selected Papers (1st ed. 2023)
Revathi Venkataraman, Annie Uthra, Vijayan Sugumaran, R I Minu, Pethuru Raj Chelliah
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R1,807
Discovery Miles 18 070
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Out of stock
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This book constitutes the refereed and selected papers presented
during the Third International Conference on Internet of Things,
ICIoT 2022, held in Chennai, India, in April 2022. The 10
papers were thoroughly reviewed and selected from the 100 qualified
submissions. They focus on application of IoT in the field of
Computer Science and Information Technology as well as on
Industrial IoT.
Numerous advancements are being brought in and incorporated into
the cloud domain with the aim of realizing a trove of deeper and
decisive automations. Rather than discussing the cloud paradigm in
isolation, this fully updated text examines how cloud computing can
work collaboratively with other computing models to meet the needs
of evolving trends.This multi-dimensional approach encompasses the
challenges of fulfilling the storage requirements of big data, the
use of the cloud as a remote server for Internet of Things and
sensor networks, and an investigation of how cloud computing is
interlinked with other established computing phenomenon such as
edge computing. New chapters illustrate the distinct
ideals of the cloud-native computing, proclaimed as the
next-generation cloud computing paradigm. Topics and features:
Includes learning objectives, motivating questions, and self-test
exercises Introduces the underlying concepts, fundamental features,
and key technological foundations of cloud computing Examines how
enterprise networking and cloud networking can work together to
achieve business goals Reviews the different types of cloud storage
available to address the evolution of data and the need for
digitization Discusses the challenges and approaches to
implementing cloud governance, security, and the hot topic of cloud
management Describes the details of cloud migration, the crucial
role of monitoring in optimizing the cloud, and the basics of
disaster recovery using cloud infrastructure This technically
rigorous, yet simple-to-follow textbook is an ideal resource for
graduate courses on cloud computing. Professional software
developers and cloud architects will also find the work to be an
invaluable reference.
Create, deploy, and manage applications at scale using SRE
principles Key Features Build and run highly available, scalable,
and secure software Explore abstract SRE in a simplified and
streamlined way Enhance the reliability of cloud environments
through SRE enhancements Book DescriptionSite reliability
engineering (SRE) is being touted as the most competent paradigm in
establishing and ensuring next-generation high-quality software
solutions. This book starts by introducing you to the SRE paradigm
and covers the need for highly reliable IT platforms and
infrastructures. As you make your way through the next set of
chapters, you will learn to develop microservices using Spring Boot
and make use of RESTful frameworks. You will also learn about
GitHub for deployment, containerization, and Docker containers.
Practical Site Reliability Engineering teaches you to set up and
sustain containerized cloud environments, and also covers
architectural and design patterns and reliability implementation
techniques such as reactive programming, and languages such as
Ballerina and Rust. In the concluding chapters, you will get
well-versed with service mesh solutions such as Istio and Linkerd,
and understand service resilience test practices, API gateways, and
edge/fog computing. By the end of this book, you will have gained
experience on working with SRE concepts and be able to deliver
highly reliable apps and services. What you will learn Understand
how to achieve your SRE goals Grasp Docker-enabled containerization
concepts Leverage enterprise DevOps capabilities and Microservices
architecture (MSA) Get to grips with the service mesh concept and
frameworks such as Istio and Linkerd Discover best practices for
performance and resiliency Follow software reliability prediction
approaches and enable patterns Understand Kubernetes for container
and cloud orchestration Explore the end-to-end software engineering
process for the containerized world Who this book is forPractical
Site Reliability Engineering helps software developers, IT
professionals, DevOps engineers, performance specialists, and
system engineers understand how the emerging domain of SRE comes
handy in automating and accelerating the process of designing,
developing, debugging, and deploying highly reliable applications
and services.
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