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Book Learning Apache Apex

    Book Details:
  • Author : Thomas Weise
  • Publisher : Packt Publishing Ltd
  • Release : 2017-11-30
  • ISBN : 1788294114
  • Pages : 282 pages

Download or read book Learning Apache Apex written by Thomas Weise and published by Packt Publishing Ltd. This book was released on 2017-11-30 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing and writing a real-time streaming publication with Apache Apex About This Book Get a clear, practical approach to real-time data processing Program Apache Apex streaming applications This book shows you Apex integration with the open source Big Data ecosystem Who This Book Is For This book assumes knowledge of application development with Java and familiarity with distributed systems. Familiarity with other real-time streaming frameworks is not required, but some practical experience with other big data processing utilities might be helpful. What You Will Learn Put together a functioning Apex application from scratch Scale an Apex application and configure it for optimal performance Understand how to deal with failures via the fault tolerance features of the platform Use Apex via other frameworks such as Beam Understand the DevOps implications of deploying Apex In Detail Apache Apex is a next-generation stream processing framework designed to operate on data at large scale, with minimum latency, maximum reliability, and strict correctness guarantees. Half of the book consists of Apex applications, showing you key aspects of data processing pipelines such as connectors for sources and sinks, and common data transformations. The other half of the book is evenly split into explaining the Apex framework, and tuning, testing, and scaling Apex applications. Much of our economic world depends on growing streams of data, such as social media feeds, financial records, data from mobile devices, sensors and machines (the Internet of Things - IoT). The projects in the book show how to process such streams to gain valuable, timely, and actionable insights. Traditional use cases, such as ETL, that currently consume a significant chunk of data engineering resources are also covered. The final chapter shows you future possibilities emerging in the streaming space, and how Apache Apex can contribute to it. Style and approach This book is divided into two major parts: first it explains what Apex is, what its relevant parts are, and how to write well-built Apex applications. The second part is entirely application-driven, walking you through Apex applications of increasing complexity.

Book Learning Apache Apex

Download or read book Learning Apache Apex written by Thomas Weise and published by . This book was released on 2017-11-30 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing and writing a real-time streaming publication with Apache ApexAbout This Book* Get a clear, practical approach to real-time data processing* Program Apache Apex streaming applications* This book shows you Apex integration with the open source Big Data ecosystemWho This Book Is ForThis book assumes knowledge of application development with Java and familiarity with distributed systems. Familiarity with other real-time streaming frameworks is not required, but some practical experience with other big data processing utilities might be helpful.What You Will Learn* Put together a functioning Apex application from scratch* Scale an Apex application and configure it for optimal performance* Understand how to deal with failures via the fault tolerance features of the platform* Use Apex via other frameworks such as Beam* Understand the DevOps implications of deploying ApexIn DetailApache Apex is a next-generation stream processing framework designed to operate on data at large scale, with minimum latency, maximum reliability, and strict correctness guarantees.Half of the book consists of Apex applications, showing you key aspects of data processing pipelines such as connectors for sources and sinks, and common data transformations. The other half of the book is evenly split into explaining the Apex framework, and tuning, testing, and scaling Apex applications.Much of our economic world depends on growing streams of data, such as social media feeds, financial records, data from mobile devices, sensors and machines (the Internet of Things - IoT). The projects in the book show how to process such streams to gain valuable, timely, and actionable insights. Traditional use cases, such as ETL, that currently consume a significant chunk of data engineering resources are also covered.The final chapter shows you future possibilities emerging in the streaming space, and how Apache Apex can contribute to it.Style and approachThis book is divided into two major parts: first it explains what Apex is, what its relevant parts are, and how to write well-built Apex applications. The second part is entirely application-driven, walking you through Apex applications of increasing complexity.

Book Building Machine Learning and Deep Learning Models on Google Cloud Platform

Download or read book Building Machine Learning and Deep Learning Models on Google Cloud Platform written by Ekaba Bisong and published by Apress. This book was released on 2019-09-27 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform. Author Ekaba Bisong shows you how machine learning tools and techniques are used to predict or classify events based on a set of interactions between variables known as features or attributes in a particular dataset. He teaches you how deep learning extends the machine learning algorithm of neural networks to learn complex tasks that are difficult for computers to perform, such as recognizing faces and understanding languages. And you will know how to leverage cloud computing to accelerate data science and machine learning deployments. Building Machine Learning and Deep Learning Models on Google Cloud Platform is divided into eight parts that cover the fundamentals of machine learning and deep learning, the concept of data science and cloud services, programming for data science using the Python stack, Google Cloud Platform (GCP) infrastructure and products, advanced analytics on GCP, and deploying end-to-end machine learning solution pipelines on GCP. What You’ll Learn Understand the principles and fundamentals of machine learning and deep learning, the algorithms, how to use them, when to use them, and how to interpret your resultsKnow the programming concepts relevant to machine and deep learning design and development using the Python stack Build and interpret machine and deep learning models Use Google Cloud Platform tools and services to develop and deploy large-scale machine learning and deep learning products Be aware of the different facets and design choices to consider when modeling a learning problem Productionalize machine learning models into software products Who This Book Is For Beginners to the practice of data science and applied machine learning, data scientists at all levels, machine learning engineers, Google Cloud Platform data engineers/architects, and software developers

Book Handbook of Research on Engineering Education in a Global Context

Download or read book Handbook of Research on Engineering Education in a Global Context written by Smirnova, Elena V. and published by IGI Global. This book was released on 2018-08-31 with total page 657 pages. Available in PDF, EPUB and Kindle. Book excerpt: Engineering education methods and standards are important features of engineering programs that should be carefully designed both to provide students and stakeholders with valuable, active, integrated learning experiences, and to provide a vehicle for assessing program outcomes. With the driving force of the globalization of the engineering profession, standards should be developed for mutual recognition of engineering education across the world, but it is proving difficult to achieve. The Handbook of Research on Engineering Education in a Global Context provides innovative insights into the importance of quality training and preparation for engineering students. It explores the common and current problems encountered in areas such as quality and standards, management information systems, innovation and enhanced learning technologies in education, as well as the challenges of employability, entrepreneurship, and diversity. This publication is vital reference source for science and engineering educators, engineering professionals, and educational administrators interested in topics centered on the education of students in the field of engineering.

Book Big Data Computing

    Book Details:
  • Author : Tanvir Habib Sardar
  • Publisher : CRC Press
  • Release : 2024-02-27
  • ISBN : 100382272X
  • Pages : 397 pages

Download or read book Big Data Computing written by Tanvir Habib Sardar and published by CRC Press. This book was released on 2024-02-27 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book primarily aims to provide an in-depth understanding of recent advances in big data computing technologies, methodologies, and applications along with introductory details of big data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and big data streaming services such as Apache Spark, Kafka, and so forth. It also covers developments in big data computing applications such as machine learning, deep learning, graph processing, and many others. Features: Provides comprehensive analysis of advanced aspects of big data challenges and enabling technologies. Explains computing models using real-world examples and dataset-based experiments. Includes case studies, quality diagrams, and demonstrations in each chapter. Describes modifications and optimization of existing technologies along with the novel big data computing models. Explores references to machine learning, deep learning, and graph processing. This book is aimed at graduate students and researchers in high-performance computing, data mining, knowledge discovery, and distributed computing.

Book The Cloud Based Demand Driven Supply Chain

Download or read book The Cloud Based Demand Driven Supply Chain written by Vinit Sharma and published by John Wiley & Sons. This book was released on 2018-11-08 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: It’s time to get your head in the cloud! In today’s business environment, more and more people are requesting cloud-based solutions to help solve their business challenges. So how can you not only anticipate your clients’ needs but also keep ahead of the curve to ensure their goals stay on track? With the help of this accessible book, you’ll get a clear sense of cloud computing and understand how to communicate the benefits, drawbacks, and options to your clients so they can make the best choices for their unique needs. Plus, case studies give you the opportunity to relate real-life examples of how the latest technologies are giving organizations worldwide the opportunity to thrive as supply chain solutions in the cloud. Demonstrates how improvements in forecasting, collaboration, and inventory optimization can lead to cost savings Explores why cloud computing is becoming increasingly important Takes a close look at the types of cloud computing Makes sense of demand-driven forecasting using Amazon's cloud Whether you work in management, business, or IT, this is the dog-eared reference you’ll want to keep close by as you continue making sense of the cloud.

Book Agile and Lean Concepts for Teaching and Learning

Download or read book Agile and Lean Concepts for Teaching and Learning written by David Parsons and published by Springer. This book was released on 2018-10-24 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the application of agile and lean techniques, originally from the field of software development and manufacturing, to various aspects of education. It covers a broad range of topics, including applying agile teaching and learning techniques in the classroom, incorporating lean thinking in educational workflows, and using team-based approaches to student-centred activities based on agile principles and processes. Demonstrating how agile and lean ideas can concretely be applied to education, the book offers practical guidance on how to apply these ideas in the classroom or lecture hall, as well as new concepts that could spark further research and development.

Book Learning Salesforce Development with Apex

Download or read book Learning Salesforce Development with Apex written by Paul Battisson and published by BPB Publications. This book was released on 2022-08-12 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to harness the power of the Apex language to build Salesforce applications DESCRIPTION Acquiring knowledge of Apex has proved to be a valuable skill for developers eager to add business logic, as well as to execute flow and transaction control statements on Salesforce server. In this updated and expanded second edition, Author Paul Battisson places a significant emphasis on the scalability, security, and deployment capabilities of Salesforce applications. The nine-time Salesforce MVP took another shot at teaching Apex programming and getting people to start developing Salesforce applications with complete confidence. Some of the most notable features of this newer edition are: -Setting up the Salesforce development environment and improving code storage and execution techniques. -Writing secure Apex code and different ways to enforce security while scaling applications. -Multiple ways to put your Apex code into production. -Acquire working knowledge of declaring variables in Apex. -Recognize Apex's collection-based functionality. -Use Apex's different control statements to manage the flow of a program. -Get familiar with Apex's built-in testing tools. -Acquire proficiency in interacting with third-party applications and data. -A quick rundown on successfully operating and managing CI/CD and DevOps. -Expert-run approaches and best practices to write robust codes and avoid major mistakes. The book contains updates on several sections of this book, including but not limited to programming principles, the use of REST APIs, code testing, and simple examples to assist you in developing dynamic solutions and creating a platform to build. WHO THIS BOOK IS FOR Both new and experienced Salesforce administrators can benefit from this book. Those who have no previous programming knowledge can also benefit from this book. The reader is anticipated to have a basic understanding of Salesforce as a platform. TABLE OF CONTENTS 1. An Introduction to the Salesforce Platform 2. What is Apex? 3. Variables in Apex 4. Collections 5. Control Statements and Operators 6. Apex Triggers 7. SOQL 8. SOSL 9. Apex Classes 10. Apex Class Inheritance 11. Enforcing Security in Apex 12. Testing Apex 13. Callouts in Apex 14. Deploying Your Apex Code 15. Apex Best Practices 16. Conclusion

Book Learning from Data Streams in Evolving Environments

Download or read book Learning from Data Streams in Evolving Environments written by Moamar Sayed-Mouchaweh and published by Springer. This book was released on 2018-07-28 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field. Provides multiple examples to facilitate the understanding data streams in non-stationary environments; Presents several application cases to show how the methods solve different real world problems; Discusses the links between methods to help stimulate new research and application directions.

Book Disruptive Analytics

    Book Details:
  • Author : Thomas W. Dinsmore
  • Publisher : Apress
  • Release : 2016-08-27
  • ISBN : 1484213114
  • Pages : 276 pages

Download or read book Disruptive Analytics written by Thomas W. Dinsmore and published by Apress. This book was released on 2016-08-27 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn all you need to know about seven key innovations disrupting business analytics today. These innovations—the open source business model, cloud analytics, the Hadoop ecosystem, Spark and in-memory analytics, streaming analytics, Deep Learning, and self-service analytics—are radically changing how businesses use data for competitive advantage. Taken together, they are disrupting the business analytics value chain, creating new opportunities. Enterprises who seize the opportunity will thrive and prosper, while others struggle and decline: disrupt or be disrupted. Disruptive Business Analytics provides strategies to profit from disruption. It shows you how to organize for insight, build and provision an open source stack, how to practice lean data warehousing, and how to assimilate disruptive innovations into an organization. Through a short history of business analytics and a detailed survey of products and services, analytics authority Thomas W. Dinsmore provides a practical explanation of the most compelling innovations available today. What You'll Learn Discover how the open source business model works and how to make it work for you See how cloud computing completely changes the economics of analytics Harness the power of Hadoop and its ecosystem Find out why Apache Spark is everywhere Discover the potential of streaming and real-time analytics Learn what Deep Learning can do and why it matters See how self-service analytics can change the way organizations do business Who This Book Is For Corporate actors at all levels of responsibility for analytics: analysts, CIOs, CTOs, strategic decision makers, managers, systems architects, technical marketers, product developers, IT personnel, and consultants.

Book Off Board Car Diagnostics Based on Heterogeneous  Highly Imbalanced and High Dimensional Data Using Machine Learning Techniques

Download or read book Off Board Car Diagnostics Based on Heterogeneous Highly Imbalanced and High Dimensional Data Using Machine Learning Techniques written by Bernhard Schlegel and published by kassel university press GmbH. This book was released on 2019-08-16 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Internet of Things A to Z

Download or read book Internet of Things A to Z written by Qusay F. Hassan and published by John Wiley & Sons. This book was released on 2018-05-09 with total page 706 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of the Internet of Things’ core concepts, technologies, and applications Internet of Things A to Z offers a holistic approach to the Internet of Things (IoT) model. The Internet of Things refers to uniquely identifiable objects and their virtual representations in an Internet-like structure. Recently, there has been a rapid growth in research on IoT communications and networks, that confirms the scalability and broad reach of the core concepts. With contributions from a panel of international experts, the text offers insight into the ideas, technologies, and applications of this subject. The authors discuss recent developments in the field and the most current and emerging trends in IoT. In addition, the text is filled with examples of innovative applications and real-world case studies. Internet of Things A to Z fills the need for an up-to-date volume on the topic. This important book: Covers in great detail the core concepts, enabling technologies, and implications of the Internet of Things Addresses the business, social, and legal aspects of the Internet of Things Explores the critical topic of security and privacy challenges for both individuals and organizations Includes a discussion of advanced topics such as the need for standards and interoperability Contains contributions from an international group of experts in academia, industry, and research Written for ICT researchers, industry professionals, and lifetime IT learners as well as academics and students, Internet of Things A to Z provides a much-needed and comprehensive resource to this burgeoning field.

Book Apache Hadoop 3 Quick Start Guide

Download or read book Apache Hadoop 3 Quick Start Guide written by Hrishikesh Vijay Karambelkar and published by Packt Publishing Ltd. This book was released on 2018-10-31 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fast paced guide that will help you learn about Apache Hadoop 3 and its ecosystem Key FeaturesSet up, configure and get started with Hadoop to get useful insights from large data setsWork with the different components of Hadoop such as MapReduce, HDFS and YARN Learn about the new features introduced in Hadoop 3Book Description Apache Hadoop is a widely used distributed data platform. It enables large datasets to be efficiently processed instead of using one large computer to store and process the data. This book will get you started with the Hadoop ecosystem, and introduce you to the main technical topics, including MapReduce, YARN, and HDFS. The book begins with an overview of big data and Apache Hadoop. Then, you will set up a pseudo Hadoop development environment and a multi-node enterprise Hadoop cluster. You will see how the parallel programming paradigm, such as MapReduce, can solve many complex data processing problems. The book also covers the important aspects of the big data software development lifecycle, including quality assurance and control, performance, administration, and monitoring. You will then learn about the Hadoop ecosystem, and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Finally, you will look at advanced topics, including real time streaming using Apache Storm, and data analytics using Apache Spark. By the end of the book, you will be well versed with different configurations of the Hadoop 3 cluster. What you will learnStore and analyze data at scale using HDFS, MapReduce and YARNInstall and configure Hadoop 3 in different modesUse Yarn effectively to run different applications on Hadoop based platformUnderstand and monitor how Hadoop cluster is managedConsume streaming data using Storm, and then analyze it using SparkExplore Apache Hadoop ecosystem components, such as Flume, Sqoop, HBase, Hive, and KafkaWho this book is for Aspiring Big Data professionals who want to learn the essentials of Hadoop 3 will find this book to be useful. Existing Hadoop users who want to get up to speed with the new features introduced in Hadoop 3 will also benefit from this book. Having knowledge of Java programming will be an added advantage.

Book Beginning Apache Spark 2

Download or read book Beginning Apache Spark 2 written by Hien Luu and published by Apress. This book was released on 2018-08-16 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop applications for the big data landscape with Spark and Hadoop. This book also explains the role of Spark in developing scalable machine learning and analytics applications with Cloud technologies. Beginning Apache Spark 2 gives you an introduction to Apache Spark and shows you how to work with it. Along the way, you’ll discover resilient distributed datasets (RDDs); use Spark SQL for structured data; and learn stream processing and build real-time applications with Spark Structured Streaming. Furthermore, you’ll learn the fundamentals of Spark ML for machine learning and much more. After you read this book, you will have the fundamentals to become proficient in using Apache Spark and know when and how to apply it to your big data applications. What You Will Learn Understand Spark unified data processing platform How to run Spark in Spark Shell or Databricks Use and manipulate RDDs Deal with structured data using Spark SQL through its operations and advanced functions Build real-time applications using Spark Structured Streaming Develop intelligent applications with the Spark Machine Learning library Who This Book Is For Programmers and developers active in big data, Hadoop, and Java but who are new to the Apache Spark platform.

Book Learning Salesforce Einstein

Download or read book Learning Salesforce Einstein written by Mohith Shrivastava and published by Packt Publishing Ltd. This book was released on 2017-06-28 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Incorporate the power of Einstein in your Salesforce application About This Book Make better predictions of your business processes using prediction and predictive modeling Build your own custom models by leveraging PredictionIO on the Heroku platform Integrate Einstein into various cloud services to predict sales, marketing leads, insights into news feeds, and more Who This Book Is For This book is for developers, data scientists, and Salesforce-experienced consultants who want to explore Salesforce Einstein and its current offerings. It assumes some prior experience with the Salesforce platform. What You Will Learn Get introduced to AI and its role in CRM and cloud applications Understand how Einstein works for the sales, service, marketing, community, and commerce clouds Gain a deep understanding of how to use Einstein for the analytics cloud Build predictive apps on Heroku using PredictionIO, and work with Einstein Predictive Vision Services Incorporate Einstein in the IoT cloud Test the accuracy of Einstein through Salesforce reporting and Wave analytics In Detail Dreamforce 16 brought forth the latest addition to the Salesforce platform: an AI tool named Einstein. Einstein promises to provide users of all Salesforce applications with a powerful platform to help them gain deep insights into the data they work on. This book will introduce you to Einstein and help you integrate it into your respective business applications based on the Salesforce platform. We start off with an introduction to AI, then move on to look at how AI can make your CRM and apps smarter. Next, we discuss various out-of-the-box components added to sales, service, marketing, and community clouds from salesforce to add Artificial Intelligence capabilities. Further on, we teach you how to use Heroku, PredictionIO, and the force.com platform, along with Einstein, to build smarter apps. The core chapters focus on developer content and introduce PredictionIO and Salesforce Einstein Vision Services. We explore Einstein Predictive Vision Services, along with analytics cloud, the Einstein Data Discovery product, and IOT core concepts. Throughout the book, we also focus on how Einstein can be integrated into CRM and various clouds such as sales, services, marketing, and communities. By the end of the book, you will be able to embrace and leverage the power of Einstein, incorporating its functions to gain more knowledge. Salesforce developers will be introduced to the world of AI, while data scientists will gain insights into Salesforce's various cloud offerings and how they can use Einstein's capabilities and enhance applications. Style and approach This book takes a straightforward approach to explain Salesforce Einstein and all of its potential applications. Filled with examples, the book presents the facts along with seasoned advice and real-world use cases to ensure you have all the resources you need to incorporate the power of Einstein in your work.

Book Spark

    Book Details:
  • Author : Ilya Ganelin
  • Publisher : John Wiley & Sons
  • Release : 2016-03-04
  • ISBN : 1119254043
  • Pages : 216 pages

Download or read book Spark written by Ilya Ganelin and published by John Wiley & Sons. This book was released on 2016-03-04 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Production-targeted Spark guidance with real-world use cases Spark: Big Data Cluster Computing in Production goes beyond general Spark overviews to provide targeted guidance toward using lightning-fast big-data clustering in production. Written by an expert team well-known in the big data community, this book walks you through the challenges in moving from proof-of-concept or demo Spark applications to live Spark in production. Real use cases provide deep insight into common problems, limitations, challenges, and opportunities, while expert tips and tricks help you get the most out of Spark performance. Coverage includes Spark SQL, Tachyon, Kerberos, ML Lib, YARN, and Mesos, with clear, actionable guidance on resource scheduling, db connectors, streaming, security, and much more. Spark has become the tool of choice for many Big Data problems, with more active contributors than any other Apache Software project. General introductory books abound, but this book is the first to provide deep insight and real-world advice on using Spark in production. Specific guidance, expert tips, and invaluable foresight make this guide an incredibly useful resource for real production settings. Review Spark hardware requirements and estimate cluster size Gain insight from real-world production use cases Tighten security, schedule resources, and fine-tune performance Overcome common problems encountered using Spark in production Spark works with other big data tools including MapReduce and Hadoop, and uses languages you already know like Java, Scala, Python, and R. Lightning speed makes Spark too good to pass up, but understanding limitations and challenges in advance goes a long way toward easing actual production implementation. Spark: Big Data Cluster Computing in Production tells you everything you need to know, with real-world production insight and expert guidance, tips, and tricks.

Book Cloud Computing for Machine Learning and Cognitive Applications

Download or read book Cloud Computing for Machine Learning and Cognitive Applications written by Kai Hwang and published by MIT Press. This book was released on 2017-07-07 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first textbook to teach students how to build data analytic solutions on large data sets using cloud-based technologies. This is the first textbook to teach students how to build data analytic solutions on large data sets (specifically in Internet of Things applications) using cloud-based technologies for data storage, transmission and mashup, and AI techniques to analyze this data. This textbook is designed to train college students to master modern cloud computing systems in operating principles, architecture design, machine learning algorithms, programming models and software tools for big data mining, analytics, and cognitive applications. The book will be suitable for use in one-semester computer science or electrical engineering courses on cloud computing, machine learning, cloud programming, cognitive computing, or big data science. The book will also be very useful as a reference for professionals who want to work in cloud computing and data science. Cloud and Cognitive Computing begins with two introductory chapters on fundamentals of cloud computing, data science, and adaptive computing that lay the foundation for the rest of the book. Subsequent chapters cover topics including cloud architecture, mashup services, virtual machines, Docker containers, mobile clouds, IoT and AI, inter-cloud mashups, and cloud performance and benchmarks, with a focus on Google's Brain Project, DeepMind, and X-Lab programs, IBKai HwangM SyNapse, Bluemix programs, cognitive initiatives, and neurocomputers. The book then covers machine learning algorithms and cloud programming software tools and application development, applying the tools in machine learning, social media, deep learning, and cognitive applications. All cloud systems are illustrated with big data and cognitive application examples.